Merge branch 'router-for-me:main' into main

fix(kiro): remove the extra quotation marks from the protocol handler

config.example.yaml

@@ -151,8 +151,8 @@ ws-auth: false
 #   upstream-url: "https://ampcode.com"
 #   # Optional: Override API key for Amp upstream (otherwise uses env or file)
 #   upstream-api-key: ""
-#   # Restrict Amp management routes (/api/auth, /api/user, etc.) to localhost only (recommended)
-#   restrict-management-to-localhost: true
+#   # Restrict Amp management routes (/api/auth, /api/user, etc.) to localhost only (default: false)
+#   restrict-management-to-localhost: false
 #   # Force model mappings to run before checking local API keys (default: false)
 #   force-model-mappings: false
 #   # Amp Model Mappings

internal/api/handlers/management/auth_files.go

@@ -30,6 +30,7 @@ import (
 	"github.com/router-for-me/CLIProxyAPI/v6/internal/auth/qwen"
 	"github.com/router-for-me/CLIProxyAPI/v6/internal/interfaces"
 	"github.com/router-for-me/CLIProxyAPI/v6/internal/misc"
+	"github.com/router-for-me/CLIProxyAPI/v6/internal/registry"
 	"github.com/router-for-me/CLIProxyAPI/v6/internal/util"
 	sdkAuth "github.com/router-for-me/CLIProxyAPI/v6/sdk/auth"
 	coreauth "github.com/router-for-me/CLIProxyAPI/v6/sdk/cliproxy/auth"
@@ -293,6 +294,54 @@ func (h *Handler) ListAuthFiles(c *gin.Context) {
 	c.JSON(200, gin.H{"files": files})
 }
 
+// GetAuthFileModels returns the models supported by a specific auth file
+func (h *Handler) GetAuthFileModels(c *gin.Context) {
+	name := c.Query("name")
+	if name == "" {
+		c.JSON(400, gin.H{"error": "name is required"})
+		return
+	}
+
+	// Try to find auth ID via authManager
+	var authID string
+	if h.authManager != nil {
+		auths := h.authManager.List()
+		for _, auth := range auths {
+			if auth.FileName == name || auth.ID == name {
+				authID = auth.ID
+				break
+			}
+		}
+	}
+
+	if authID == "" {
+		authID = name // fallback to filename as ID
+	}
+
+	// Get models from registry
+	reg := registry.GetGlobalRegistry()
+	models := reg.GetModelsForClient(authID)
+
+	result := make([]gin.H, 0, len(models))
+	for _, m := range models {
+		entry := gin.H{
+			"id": m.ID,
+		}
+		if m.DisplayName != "" {
+			entry["display_name"] = m.DisplayName
+		}
+		if m.Type != "" {
+			entry["type"] = m.Type
+		}
+		if m.OwnedBy != "" {
+			entry["owned_by"] = m.OwnedBy
+		}
+		result = append(result, entry)
+	}
+
+	c.JSON(200, gin.H{"models": result})
+}
+
 // List auth files from disk when the auth manager is unavailable.
 func (h *Handler) listAuthFilesFromDisk(c *gin.Context) {
 	entries, err := os.ReadDir(h.cfg.AuthDir)

internal/api/modules/amp/amp.go

@@ -137,7 +137,8 @@ func (m *AmpModule) Register(ctx modules.Context) error {
 		m.registerProviderAliases(ctx.Engine, ctx.BaseHandler, auth)
 
 		// Register management proxy routes once; middleware will gate access when upstream is unavailable.
-		m.registerManagementRoutes(ctx.Engine, ctx.BaseHandler)
+		// Pass auth middleware to require valid API key for all management routes.
+		m.registerManagementRoutes(ctx.Engine, ctx.BaseHandler, auth)
 
 		// If no upstream URL, skip proxy routes but provider aliases are still available
 		if upstreamURL == "" {
@@ -187,9 +188,6 @@ func (m *AmpModule) OnConfigUpdated(cfg *config.Config) error {
 
 	if oldSettings != nil && oldSettings.RestrictManagementToLocalhost != newSettings.RestrictManagementToLocalhost {
 		m.setRestrictToLocalhost(newSettings.RestrictManagementToLocalhost)
-		if !newSettings.RestrictManagementToLocalhost {
-			log.Warnf("amp management routes now accessible from any IP - this is insecure!")
-		}
 	}
 
 	newUpstreamURL := strings.TrimSpace(newSettings.UpstreamURL)

internal/api/modules/amp/fallback_handlers.go

@@ -64,7 +64,7 @@ func logAmpRouting(routeType AmpRouteType, requestedModel, resolvedModel, provid
 		fields["cost"] = "amp_credits"
 		fields["source"] = "ampcode.com"
 		fields["model_id"] = requestedModel // Explicit model_id for easy config reference
-		log.WithFields(fields).Warnf("forwarding to ampcode.com (uses amp credits) - model_id: %s | To use local proxy, add to config: amp-model-mappings: [{from: \"%s\", to: \"<your-local-model>\"}]", requestedModel, requestedModel)
+		log.WithFields(fields).Warnf("forwarding to ampcode.com (uses amp credits) - model_id: %s | To use local provider, add to config: ampcode.model-mappings: [{from: \"%s\", to: \"<your-local-model>\"}]", requestedModel, requestedModel)
 
 	case RouteTypeNoProvider:
 		fields["cost"] = "none"

internal/api/modules/amp/proxy.go

@@ -44,6 +44,11 @@ func createReverseProxy(upstreamURL string, secretSource SecretSource) (*httputi
 		originalDirector(req)
 		req.Host = parsed.Host
 
+		// Remove client's Authorization header - it was only used for CLI Proxy API authentication
+		// We will set our own Authorization using the configured upstream-api-key
+		req.Header.Del("Authorization")
+		req.Header.Del("X-Api-Key")
+
 		// Preserve correlation headers for debugging
 		if req.Header.Get("X-Request-ID") == "" {
 			// Could generate one here if needed
@@ -53,7 +58,7 @@ func createReverseProxy(upstreamURL string, secretSource SecretSource) (*httputi
 		// Users going through ampcode.com proxy are paying for the service and should get all features
 		// including 1M context window (context-1m-2025-08-07)
 
-		// Inject API key from secret source (precedence: config > env > file)
+		// Inject API key from secret source (only uses upstream-api-key from config)
 		if key, err := secretSource.Get(req.Context()); err == nil && key != "" {
 			req.Header.Set("X-Api-Key", key)
 			req.Header.Set("Authorization", fmt.Sprintf("Bearer %s", key))

internal/api/modules/amp/response_rewriter.go

@@ -29,17 +29,79 @@ func NewResponseRewriter(w gin.ResponseWriter, originalModel string) *ResponseRe
 	}
 }
 
+const maxBufferedResponseBytes = 2 * 1024 * 1024 // 2MB safety cap
+
+func looksLikeSSEChunk(data []byte) bool {
+	// Fallback detection: some upstreams may omit/lie about Content-Type, causing SSE to be buffered.
+	// Heuristics are intentionally simple and cheap.
+	return bytes.Contains(data, []byte("data:")) ||
+		bytes.Contains(data, []byte("event:")) ||
+		bytes.Contains(data, []byte("message_start")) ||
+		bytes.Contains(data, []byte("message_delta")) ||
+		bytes.Contains(data, []byte("content_block_start")) ||
+		bytes.Contains(data, []byte("content_block_delta")) ||
+		bytes.Contains(data, []byte("content_block_stop")) ||
+		bytes.Contains(data, []byte("\n\n"))
+}
+
+func (rw *ResponseRewriter) enableStreaming(reason string) error {
+	if rw.isStreaming {
+		return nil
+	}
+	rw.isStreaming = true
+
+	// Flush any previously buffered data to avoid reordering or data loss.
+	if rw.body != nil && rw.body.Len() > 0 {
+		buf := rw.body.Bytes()
+		// Copy before Reset() to keep bytes stable.
+		toFlush := make([]byte, len(buf))
+		copy(toFlush, buf)
+		rw.body.Reset()
+
+		if _, err := rw.ResponseWriter.Write(rw.rewriteStreamChunk(toFlush)); err != nil {
+			return err
+		}
+		if flusher, ok := rw.ResponseWriter.(http.Flusher); ok {
+			flusher.Flush()
+		}
+	}
+
+	log.Debugf("amp response rewriter: switched to streaming (%s)", reason)
+	return nil
+}
+
 // Write intercepts response writes and buffers them for model name replacement
 func (rw *ResponseRewriter) Write(data []byte) (int, error) {
-	// Detect streaming on first write
-	if rw.body.Len() == 0 && !rw.isStreaming {
+	// Detect streaming on first write (header-based)
+	if !rw.isStreaming && rw.body.Len() == 0 {
 		contentType := rw.Header().Get("Content-Type")
 		rw.isStreaming = strings.Contains(contentType, "text/event-stream") ||
 			strings.Contains(contentType, "stream")
 	}
 
+	if !rw.isStreaming {
+		// Content-based fallback: detect SSE-like chunks even if Content-Type is missing/wrong.
+		if looksLikeSSEChunk(data) {
+			if err := rw.enableStreaming("sse heuristic"); err != nil {
+				return 0, err
+			}
+		} else if rw.body.Len()+len(data) > maxBufferedResponseBytes {
+			// Safety cap: avoid unbounded buffering on large responses.
+			log.Warnf("amp response rewriter: buffer exceeded %d bytes, switching to streaming", maxBufferedResponseBytes)
+			if err := rw.enableStreaming("buffer limit"); err != nil {
+				return 0, err
+			}
+		}
+	}
+
 	if rw.isStreaming {
-		return rw.ResponseWriter.Write(rw.rewriteStreamChunk(data))
+		n, err := rw.ResponseWriter.Write(rw.rewriteStreamChunk(data))
+		if err == nil {
+			if flusher, ok := rw.ResponseWriter.(http.Flusher); ok {
+				flusher.Flush()
+			}
+		}
+		return n, err
 	}
 	return rw.body.Write(data)
 }

internal/api/modules/amp/routes.go

@@ -98,7 +98,8 @@ func (m *AmpModule) managementAvailabilityMiddleware() gin.HandlerFunc {
 // registerManagementRoutes registers Amp management proxy routes
 // These routes proxy through to the Amp control plane for OAuth, user management, etc.
 // Uses dynamic middleware and proxy getter for hot-reload support.
-func (m *AmpModule) registerManagementRoutes(engine *gin.Engine, baseHandler *handlers.BaseAPIHandler) {
+// The auth middleware validates Authorization header against configured API keys.
+func (m *AmpModule) registerManagementRoutes(engine *gin.Engine, baseHandler *handlers.BaseAPIHandler, auth gin.HandlerFunc) {
 	ampAPI := engine.Group("/api")
 
 	// Always disable CORS for management routes to prevent browser-based attacks
@@ -107,8 +108,9 @@ func (m *AmpModule) registerManagementRoutes(engine *gin.Engine, baseHandler *ha
 	// Apply dynamic localhost-only restriction (hot-reloadable via m.IsRestrictedToLocalhost())
 	ampAPI.Use(m.localhostOnlyMiddleware())
 
-	if !m.IsRestrictedToLocalhost() {
-		log.Warn("amp management routes are NOT restricted to localhost - this is insecure!")
+	// Apply authentication middleware - requires valid API key in Authorization header
+	if auth != nil {
+		ampAPI.Use(auth)
 	}
 
 	// Dynamic proxy handler that uses m.getProxy() for hot-reload support
@@ -154,6 +156,9 @@ func (m *AmpModule) registerManagementRoutes(engine *gin.Engine, baseHandler *ha
 	// Root-level routes that AMP CLI expects without /api prefix
 	// These need the same security middleware as the /api/* routes (dynamic for hot-reload)
 	rootMiddleware := []gin.HandlerFunc{m.managementAvailabilityMiddleware(), noCORSMiddleware(), m.localhostOnlyMiddleware()}
+	if auth != nil {
+		rootMiddleware = append(rootMiddleware, auth)
+	}
 	engine.GET("/threads/*path", append(rootMiddleware, proxyHandler)...)
 	engine.GET("/threads.rss", append(rootMiddleware, proxyHandler)...)
 	engine.GET("/news.rss", append(rootMiddleware, proxyHandler)...)

internal/api/server.go

@@ -586,6 +586,7 @@ func (s *Server) registerManagementRoutes() {
 		mgmt.DELETE("/oauth-excluded-models", s.mgmt.DeleteOAuthExcludedModels)
 
 		mgmt.GET("/auth-files", s.mgmt.ListAuthFiles)
+		mgmt.GET("/auth-files/models", s.mgmt.GetAuthFileModels)
 		mgmt.GET("/auth-files/download", s.mgmt.DownloadAuthFile)
 		mgmt.POST("/auth-files", s.mgmt.UploadAuthFile)
 		mgmt.DELETE("/auth-files", s.mgmt.DeleteAuthFile)

internal/auth/kiro/protocol_handler.go

@@ -471,7 +471,7 @@ foreach ($port in $ports) {
 
 	// Create batch wrapper
 	batchPath := filepath.Join(scriptDir, "kiro-oauth-handler.bat")
-	batchContent := fmt.Sprintf("@echo off\npowershell -ExecutionPolicy Bypass -File \"%s\" \"%%1\"\n", scriptPath)
+	batchContent := fmt.Sprintf("@echo off\npowershell -ExecutionPolicy Bypass -File \"%s\" %%1\n", scriptPath)
 
 	if err := os.WriteFile(batchPath, []byte(batchContent), 0644); err != nil {
 		return fmt.Errorf("failed to write batch wrapper: %w", err)

internal/config/config.go

@@ -151,7 +151,7 @@ type AmpCode struct {
 
 	// RestrictManagementToLocalhost restricts Amp management routes (/api/user, /api/threads, etc.)
 	// to only accept connections from localhost (127.0.0.1, ::1). When true, prevents drive-by
-	// browser attacks and remote access to management endpoints. Default: true (recommended).
+	// browser attacks and remote access to management endpoints. Default: false (API key auth is sufficient).
 	RestrictManagementToLocalhost bool `yaml:"restrict-management-to-localhost" json:"restrict-management-to-localhost"`
 
 	// ModelMappings defines model name mappings for Amp CLI requests.
@@ -368,7 +368,7 @@ func LoadConfigOptional(configFile string, optional bool) (*Config, error) {
 	cfg.LoggingToFile = false
 	cfg.UsageStatisticsEnabled = false
 	cfg.DisableCooling = false
-	cfg.AmpCode.RestrictManagementToLocalhost = true // Default to secure: only localhost access
+	cfg.AmpCode.RestrictManagementToLocalhost = false // Default to false: API key auth is sufficient
 	cfg.IncognitoBrowser = false                     // Default to normal browser (AWS uses incognito by force)
 	if err = yaml.Unmarshal(data, &cfg); err != nil {
 		if optional {

internal/registry/model_definitions.go

@@ -648,10 +648,11 @@ func GetIFlowModels() []*ModelInfo {
 		{ID: "glm-4.6", DisplayName: "GLM-4.6", Description: "Zhipu GLM 4.6 general model", Created: 1759190400},
 		{ID: "kimi-k2", DisplayName: "Kimi-K2", Description: "Moonshot Kimi K2 general model", Created: 1752192000},
 		{ID: "kimi-k2-thinking", DisplayName: "Kimi-K2-Thinking", Description: "Moonshot Kimi K2 thinking model", Created: 1762387200, Thinking: &ThinkingSupport{Levels: []string{"low", "medium", "high"}}},
-		{ID: "deepseek-v3.2-chat", DisplayName: "DeepSeek-V3.2", Description: "DeepSeek V3.2", Created: 1764576000},
+		{ID: "deepseek-v3.2-chat", DisplayName: "DeepSeek-V3.2", Description: "DeepSeek V3.2 Chat", Created: 1764576000},
+		{ID: "deepseek-v3.2-reasoner", DisplayName: "DeepSeek-V3.2", Description: "DeepSeek V3.2 Reasoner", Created: 1764576000},
 		{ID: "deepseek-v3.2", DisplayName: "DeepSeek-V3.2-Exp", Description: "DeepSeek V3.2 experimental", Created: 1759104000},
 		{ID: "deepseek-v3.1", DisplayName: "DeepSeek-V3.1-Terminus", Description: "DeepSeek V3.1 Terminus", Created: 1756339200},
-		{ID: "deepseek-r1", DisplayName: "DeepSeek-R1", Description: "DeepSeek reasoning model R1", Created: 1737331200, Thinking: &ThinkingSupport{Levels: []string{"low", "medium", "high"}}},
+		{ID: "deepseek-r1", DisplayName: "DeepSeek-R1", Description: "DeepSeek reasoning model R1", Created: 1737331200},
 		{ID: "deepseek-v3", DisplayName: "DeepSeek-V3-671B", Description: "DeepSeek V3 671B", Created: 1734307200},
 		{ID: "qwen3-32b", DisplayName: "Qwen3-32B", Description: "Qwen3 32B", Created: 1747094400},
 		{ID: "qwen3-235b-a22b-thinking-2507", DisplayName: "Qwen3-235B-A22B-Thinking", Description: "Qwen3 235B A22B Thinking (2507)", Created: 1753401600, Thinking: &ThinkingSupport{Levels: []string{"low", "medium", "high"}}},

internal/registry/model_registry.go

@@ -90,6 +90,9 @@ type ModelRegistry struct {
 	models map[string]*ModelRegistration
 	// clientModels maps client ID to the models it provides
 	clientModels map[string][]string
+	// clientModelInfos maps client ID to a map of model ID -> ModelInfo
+	// This preserves the original model info provided by each client
+	clientModelInfos map[string]map[string]*ModelInfo
 	// clientProviders maps client ID to its provider identifier
 	clientProviders map[string]string
 	// mutex ensures thread-safe access to the registry
@@ -104,10 +107,11 @@ var registryOnce sync.Once
 func GetGlobalRegistry() *ModelRegistry {
 	registryOnce.Do(func() {
 		globalRegistry = &ModelRegistry{
-			models:          make(map[string]*ModelRegistration),
-			clientModels:    make(map[string][]string),
-			clientProviders: make(map[string]string),
-			mutex:           &sync.RWMutex{},
+			models:           make(map[string]*ModelRegistration),
+			clientModels:     make(map[string][]string),
+			clientModelInfos: make(map[string]map[string]*ModelInfo),
+			clientProviders:  make(map[string]string),
+			mutex:            &sync.RWMutex{},
 		}
 	})
 	return globalRegistry
@@ -144,6 +148,7 @@ func (r *ModelRegistry) RegisterClient(clientID, clientProvider string, models [
 		// No models supplied; unregister existing client state if present.
 		r.unregisterClientInternal(clientID)
 		delete(r.clientModels, clientID)
+		delete(r.clientModelInfos, clientID)
 		delete(r.clientProviders, clientID)
 		misc.LogCredentialSeparator()
 		return
@@ -152,7 +157,7 @@ func (r *ModelRegistry) RegisterClient(clientID, clientProvider string, models [
 	now := time.Now()
 
 	oldModels, hadExisting := r.clientModels[clientID]
-	oldProvider, _ := r.clientProviders[clientID]
+	oldProvider := r.clientProviders[clientID]
 	providerChanged := oldProvider != provider
 	if !hadExisting {
 		// Pure addition path.
@@ -161,6 +166,12 @@ func (r *ModelRegistry) RegisterClient(clientID, clientProvider string, models [
 			r.addModelRegistration(modelID, provider, model, now)
 		}
 		r.clientModels[clientID] = append([]string(nil), rawModelIDs...)
+		// Store client's own model infos
+		clientInfos := make(map[string]*ModelInfo, len(newModels))
+		for id, m := range newModels {
+			clientInfos[id] = cloneModelInfo(m)
+		}
+		r.clientModelInfos[clientID] = clientInfos
 		if provider != "" {
 			r.clientProviders[clientID] = provider
 		} else {
@@ -287,6 +298,12 @@ func (r *ModelRegistry) RegisterClient(clientID, clientProvider string, models [
 	if len(rawModelIDs) > 0 {
 		r.clientModels[clientID] = append([]string(nil), rawModelIDs...)
 	}
+	// Update client's own model infos
+	clientInfos := make(map[string]*ModelInfo, len(newModels))
+	for id, m := range newModels {
+		clientInfos[id] = cloneModelInfo(m)
+	}
+	r.clientModelInfos[clientID] = clientInfos
 	if provider != "" {
 		r.clientProviders[clientID] = provider
 	} else {
@@ -436,6 +453,7 @@ func (r *ModelRegistry) unregisterClientInternal(clientID string) {
 	}
 
 	delete(r.clientModels, clientID)
+	delete(r.clientModelInfos, clientID)
 	if hasProvider {
 		delete(r.clientProviders, clientID)
 	}
@@ -885,3 +903,44 @@ func (r *ModelRegistry) GetFirstAvailableModel(handlerType string) (string, erro
 
 	return "", fmt.Errorf("no available clients for any model in handler type: %s", handlerType)
 }
+
+// GetModelsForClient returns the models registered for a specific client.
+// Parameters:
+//   - clientID: The client identifier (typically auth file name or auth ID)
+//
+// Returns:
+//   - []*ModelInfo: List of models registered for this client, nil if client not found
+func (r *ModelRegistry) GetModelsForClient(clientID string) []*ModelInfo {
+	r.mutex.RLock()
+	defer r.mutex.RUnlock()
+
+	modelIDs, exists := r.clientModels[clientID]
+	if !exists || len(modelIDs) == 0 {
+		return nil
+	}
+
+	// Try to use client-specific model infos first
+	clientInfos := r.clientModelInfos[clientID]
+
+	seen := make(map[string]struct{})
+	result := make([]*ModelInfo, 0, len(modelIDs))
+	for _, modelID := range modelIDs {
+		if _, dup := seen[modelID]; dup {
+			continue
+		}
+		seen[modelID] = struct{}{}
+
+		// Prefer client's own model info to preserve original type/owned_by
+		if clientInfos != nil {
+			if info, ok := clientInfos[modelID]; ok && info != nil {
+				result = append(result, info)
+				continue
+			}
+		}
+		// Fallback to global registry (for backwards compatibility)
+		if reg, ok := r.models[modelID]; ok && reg.Info != nil {
+			result = append(result, reg.Info)
+		}
+	}
+	return result
+}

internal/runtime/executor/aistudio_executor.go

@@ -322,7 +322,7 @@ func (e *AIStudioExecutor) translateRequest(req cliproxyexecutor.Request, opts c
 	from := opts.SourceFormat
 	to := sdktranslator.FromString("gemini")
 	payload := sdktranslator.TranslateRequest(from, to, req.Model, bytes.Clone(req.Payload), stream)
-	payload = applyThinkingMetadata(payload, req.Metadata, req.Model)
+	payload = ApplyThinkingMetadata(payload, req.Metadata, req.Model)
 	payload = util.ApplyDefaultThinkingIfNeeded(req.Model, payload)
 	payload = util.ConvertThinkingLevelToBudget(payload)
 	payload = util.NormalizeGeminiThinkingBudget(req.Model, payload)
@@ -384,8 +384,16 @@ func ensureColonSpacedJSON(payload []byte) []byte {
 
 	for i := 0; i < len(indented); i++ {
 		ch := indented[i]
-		if ch == '"' && (i == 0 || indented[i-1] != '\\') {
-			inString = !inString
+		if ch == '"' {
+			// A quote is escaped only when preceded by an odd number of consecutive backslashes.
+			// For example: "\\\"" keeps the quote inside the string, but "\\\\" closes the string.
+			backslashes := 0
+			for j := i - 1; j >= 0 && indented[j] == '\\'; j-- {
+				backslashes++
+			}
+			if backslashes%2 == 0 {
+				inString = !inString
+			}
 		}
 
 		if !inString {

internal/runtime/executor/codex_executor.go

@@ -54,9 +54,9 @@ func (e *CodexExecutor) Execute(ctx context.Context, auth *cliproxyauth.Auth, re
 	from := opts.SourceFormat
 	to := sdktranslator.FromString("codex")
 	body := sdktranslator.TranslateRequest(from, to, req.Model, bytes.Clone(req.Payload), false)
-	body = applyReasoningEffortMetadata(body, req.Metadata, req.Model, "reasoning.effort")
-	body = normalizeThinkingConfig(body, upstreamModel)
-	if errValidate := validateThinkingConfig(body, upstreamModel); errValidate != nil {
+	body = ApplyReasoningEffortMetadata(body, req.Metadata, req.Model, "reasoning.effort", false)
+	body = NormalizeThinkingConfig(body, upstreamModel, false)
+	if errValidate := ValidateThinkingConfig(body, upstreamModel); errValidate != nil {
 		return resp, errValidate
 	}
 	body = applyPayloadConfig(e.cfg, req.Model, body)
@@ -152,9 +152,9 @@ func (e *CodexExecutor) ExecuteStream(ctx context.Context, auth *cliproxyauth.Au
 	to := sdktranslator.FromString("codex")
 	body := sdktranslator.TranslateRequest(from, to, req.Model, bytes.Clone(req.Payload), true)
 
-	body = applyReasoningEffortMetadata(body, req.Metadata, req.Model, "reasoning.effort")
-	body = normalizeThinkingConfig(body, upstreamModel)
-	if errValidate := validateThinkingConfig(body, upstreamModel); errValidate != nil {
+	body = ApplyReasoningEffortMetadata(body, req.Metadata, req.Model, "reasoning.effort", false)
+	body = NormalizeThinkingConfig(body, upstreamModel, false)
+	if errValidate := ValidateThinkingConfig(body, upstreamModel); errValidate != nil {
 		return nil, errValidate
 	}
 	body = applyPayloadConfig(e.cfg, req.Model, body)
@@ -254,7 +254,7 @@ func (e *CodexExecutor) CountTokens(ctx context.Context, auth *cliproxyauth.Auth
 
 	modelForCounting := req.Model
 
-	body = applyReasoningEffortMetadata(body, req.Metadata, req.Model, "reasoning.effort")
+	body = ApplyReasoningEffortMetadata(body, req.Metadata, req.Model, "reasoning.effort", false)
 	body, _ = sjson.SetBytes(body, "model", upstreamModel)
 	body, _ = sjson.DeleteBytes(body, "previous_response_id")
 	body, _ = sjson.SetBytes(body, "stream", false)

internal/runtime/executor/gemini_cli_executor.go

@@ -11,6 +11,8 @@ import (
 	"fmt"
 	"io"
 	"net/http"
+	"regexp"
+	"strconv"
 	"strings"
 	"time"
 
@@ -784,20 +786,45 @@ func parseRetryDelay(errorBody []byte) (*time.Duration, error) {
 	// Try to parse the retryDelay from the error response
 	// Format: error.details[].retryDelay where @type == "type.googleapis.com/google.rpc.RetryInfo"
 	details := gjson.GetBytes(errorBody, "error.details")
-	if !details.Exists() || !details.IsArray() {
-		return nil, fmt.Errorf("no error.details found")
+	if details.Exists() && details.IsArray() {
+		for _, detail := range details.Array() {
+			typeVal := detail.Get("@type").String()
+			if typeVal == "type.googleapis.com/google.rpc.RetryInfo" {
+				retryDelay := detail.Get("retryDelay").String()
+				if retryDelay != "" {
+					// Parse duration string like "0.847655010s"
+					duration, err := time.ParseDuration(retryDelay)
+					if err != nil {
+						return nil, fmt.Errorf("failed to parse duration")
+					}
+					return &duration, nil
+				}
+			}
+		}
+
+		// Fallback: try ErrorInfo.metadata.quotaResetDelay (e.g., "373.801628ms")
+		for _, detail := range details.Array() {
+			typeVal := detail.Get("@type").String()
+			if typeVal == "type.googleapis.com/google.rpc.ErrorInfo" {
+				quotaResetDelay := detail.Get("metadata.quotaResetDelay").String()
+				if quotaResetDelay != "" {
+					duration, err := time.ParseDuration(quotaResetDelay)
+					if err == nil {
+						return &duration, nil
+					}
+				}
+			}
+		}
 	}
 
-	for _, detail := range details.Array() {
-		typeVal := detail.Get("@type").String()
-		if typeVal == "type.googleapis.com/google.rpc.RetryInfo" {
-			retryDelay := detail.Get("retryDelay").String()
-			if retryDelay != "" {
-				// Parse duration string like "0.847655010s"
-				duration, err := time.ParseDuration(retryDelay)
-				if err != nil {
-					return nil, fmt.Errorf("failed to parse duration")
-				}
+	// Fallback: parse from error.message "Your quota will reset after Xs."
+	message := gjson.GetBytes(errorBody, "error.message").String()
+	if message != "" {
+		re := regexp.MustCompile(`after\s+(\d+)s\.?`)
+		if matches := re.FindStringSubmatch(message); len(matches) > 1 {
+			seconds, err := strconv.Atoi(matches[1])
+			if err == nil {
+				duration := time.Duration(seconds) * time.Second
 				return &duration, nil
 			}
 		}

internal/runtime/executor/gemini_executor.go

@@ -83,7 +83,7 @@ func (e *GeminiExecutor) Execute(ctx context.Context, auth *cliproxyauth.Auth, r
 	from := opts.SourceFormat
 	to := sdktranslator.FromString("gemini")
 	body := sdktranslator.TranslateRequest(from, to, req.Model, bytes.Clone(req.Payload), false)
-	body = applyThinkingMetadata(body, req.Metadata, req.Model)
+	body = ApplyThinkingMetadata(body, req.Metadata, req.Model)
 	body = util.ApplyDefaultThinkingIfNeeded(req.Model, body)
 	body = util.NormalizeGeminiThinkingBudget(req.Model, body)
 	body = util.StripThinkingConfigIfUnsupported(req.Model, body)
@@ -178,7 +178,7 @@ func (e *GeminiExecutor) ExecuteStream(ctx context.Context, auth *cliproxyauth.A
 	from := opts.SourceFormat
 	to := sdktranslator.FromString("gemini")
 	body := sdktranslator.TranslateRequest(from, to, req.Model, bytes.Clone(req.Payload), true)
-	body = applyThinkingMetadata(body, req.Metadata, req.Model)
+	body = ApplyThinkingMetadata(body, req.Metadata, req.Model)
 	body = util.ApplyDefaultThinkingIfNeeded(req.Model, body)
 	body = util.NormalizeGeminiThinkingBudget(req.Model, body)
 	body = util.StripThinkingConfigIfUnsupported(req.Model, body)
@@ -290,7 +290,7 @@ func (e *GeminiExecutor) CountTokens(ctx context.Context, auth *cliproxyauth.Aut
 	from := opts.SourceFormat
 	to := sdktranslator.FromString("gemini")
 	translatedReq := sdktranslator.TranslateRequest(from, to, req.Model, bytes.Clone(req.Payload), false)
-	translatedReq = applyThinkingMetadata(translatedReq, req.Metadata, req.Model)
+	translatedReq = ApplyThinkingMetadata(translatedReq, req.Metadata, req.Model)
 	translatedReq = util.StripThinkingConfigIfUnsupported(req.Model, translatedReq)
 	translatedReq = fixGeminiImageAspectRatio(req.Model, translatedReq)
 	respCtx := context.WithValue(ctx, "alt", opts.Alt)

internal/runtime/executor/iflow_executor.go

@@ -57,13 +57,13 @@ func (e *IFlowExecutor) Execute(ctx context.Context, auth *cliproxyauth.Auth, re
 	from := opts.SourceFormat
 	to := sdktranslator.FromString("openai")
 	body := sdktranslator.TranslateRequest(from, to, req.Model, bytes.Clone(req.Payload), false)
-	body = applyReasoningEffortMetadata(body, req.Metadata, req.Model, "reasoning_effort")
+	body = ApplyReasoningEffortMetadata(body, req.Metadata, req.Model, "reasoning_effort", false)
 	upstreamModel := util.ResolveOriginalModel(req.Model, req.Metadata)
 	if upstreamModel != "" {
 		body, _ = sjson.SetBytes(body, "model", upstreamModel)
 	}
-	body = normalizeThinkingConfig(body, upstreamModel)
-	if errValidate := validateThinkingConfig(body, upstreamModel); errValidate != nil {
+	body = NormalizeThinkingConfig(body, upstreamModel, false)
+	if errValidate := ValidateThinkingConfig(body, upstreamModel); errValidate != nil {
 		return resp, errValidate
 	}
 	body = applyPayloadConfig(e.cfg, req.Model, body)
@@ -148,13 +148,13 @@ func (e *IFlowExecutor) ExecuteStream(ctx context.Context, auth *cliproxyauth.Au
 	to := sdktranslator.FromString("openai")
 	body := sdktranslator.TranslateRequest(from, to, req.Model, bytes.Clone(req.Payload), true)
 
-	body = applyReasoningEffortMetadata(body, req.Metadata, req.Model, "reasoning_effort")
+	body = ApplyReasoningEffortMetadata(body, req.Metadata, req.Model, "reasoning_effort", false)
 	upstreamModel := util.ResolveOriginalModel(req.Model, req.Metadata)
 	if upstreamModel != "" {
 		body, _ = sjson.SetBytes(body, "model", upstreamModel)
 	}
-	body = normalizeThinkingConfig(body, upstreamModel)
-	if errValidate := validateThinkingConfig(body, upstreamModel); errValidate != nil {
+	body = NormalizeThinkingConfig(body, upstreamModel, false)
+	if errValidate := ValidateThinkingConfig(body, upstreamModel); errValidate != nil {
 		return nil, errValidate
 	}
 	// Ensure tools array exists to avoid provider quirks similar to Qwen's behaviour.

internal/runtime/executor/openai_compat_executor.go

@@ -59,13 +59,14 @@ func (e *OpenAICompatExecutor) Execute(ctx context.Context, auth *cliproxyauth.A
 		translated = e.overrideModel(translated, modelOverride)
 	}
 	translated = applyPayloadConfigWithRoot(e.cfg, req.Model, to.String(), "", translated)
-	translated = applyReasoningEffortMetadata(translated, req.Metadata, req.Model, "reasoning_effort")
+	allowCompat := e.allowCompatReasoningEffort(req.Model, auth)
+	translated = ApplyReasoningEffortMetadata(translated, req.Metadata, req.Model, "reasoning_effort", allowCompat)
 	upstreamModel := util.ResolveOriginalModel(req.Model, req.Metadata)
 	if upstreamModel != "" && modelOverride == "" {
 		translated, _ = sjson.SetBytes(translated, "model", upstreamModel)
 	}
-	translated = normalizeThinkingConfig(translated, upstreamModel)
-	if errValidate := validateThinkingConfig(translated, upstreamModel); errValidate != nil {
+	translated = NormalizeThinkingConfig(translated, upstreamModel, allowCompat)
+	if errValidate := ValidateThinkingConfig(translated, upstreamModel); errValidate != nil {
 		return resp, errValidate
 	}
 
@@ -154,13 +155,14 @@ func (e *OpenAICompatExecutor) ExecuteStream(ctx context.Context, auth *cliproxy
 		translated = e.overrideModel(translated, modelOverride)
 	}
 	translated = applyPayloadConfigWithRoot(e.cfg, req.Model, to.String(), "", translated)
-	translated = applyReasoningEffortMetadata(translated, req.Metadata, req.Model, "reasoning_effort")
+	allowCompat := e.allowCompatReasoningEffort(req.Model, auth)
+	translated = ApplyReasoningEffortMetadata(translated, req.Metadata, req.Model, "reasoning_effort", allowCompat)
 	upstreamModel := util.ResolveOriginalModel(req.Model, req.Metadata)
 	if upstreamModel != "" && modelOverride == "" {
 		translated, _ = sjson.SetBytes(translated, "model", upstreamModel)
 	}
-	translated = normalizeThinkingConfig(translated, upstreamModel)
-	if errValidate := validateThinkingConfig(translated, upstreamModel); errValidate != nil {
+	translated = NormalizeThinkingConfig(translated, upstreamModel, allowCompat)
+	if errValidate := ValidateThinkingConfig(translated, upstreamModel); errValidate != nil {
 		return nil, errValidate
 	}
 
@@ -325,6 +327,27 @@ func (e *OpenAICompatExecutor) resolveUpstreamModel(alias string, auth *cliproxy
 	return ""
 }
 
+func (e *OpenAICompatExecutor) allowCompatReasoningEffort(model string, auth *cliproxyauth.Auth) bool {
+	trimmed := strings.TrimSpace(model)
+	if trimmed == "" || e == nil || e.cfg == nil {
+		return false
+	}
+	compat := e.resolveCompatConfig(auth)
+	if compat == nil || len(compat.Models) == 0 {
+		return false
+	}
+	for i := range compat.Models {
+		entry := compat.Models[i]
+		if strings.EqualFold(strings.TrimSpace(entry.Alias), trimmed) {
+			return true
+		}
+		if strings.EqualFold(strings.TrimSpace(entry.Name), trimmed) {
+			return true
+		}
+	}
+	return false
+}
+
 func (e *OpenAICompatExecutor) resolveCompatConfig(auth *cliproxyauth.Auth) *config.OpenAICompatibility {
 	if auth == nil || e.cfg == nil {
 		return nil

internal/runtime/executor/payload_helpers.go

@@ -11,9 +11,9 @@ import (
 	"github.com/tidwall/sjson"
 )
 
-// applyThinkingMetadata applies thinking config from model suffix metadata (e.g., (high), (8192))
+// ApplyThinkingMetadata applies thinking config from model suffix metadata (e.g., (high), (8192))
 // for standard Gemini format payloads. It normalizes the budget when the model supports thinking.
-func applyThinkingMetadata(payload []byte, metadata map[string]any, model string) []byte {
+func ApplyThinkingMetadata(payload []byte, metadata map[string]any, model string) []byte {
 	budgetOverride, includeOverride, ok := util.ResolveThinkingConfigFromMetadata(model, metadata)
 	if !ok || (budgetOverride == nil && includeOverride == nil) {
 		return payload
@@ -45,10 +45,10 @@ func applyThinkingMetadataCLI(payload []byte, metadata map[string]any, model str
 	return util.ApplyGeminiCLIThinkingConfig(payload, budgetOverride, includeOverride)
 }
 
-// applyReasoningEffortMetadata applies reasoning effort overrides from metadata to the given JSON path.
+// ApplyReasoningEffortMetadata applies reasoning effort overrides from metadata to the given JSON path.
 // Metadata values take precedence over any existing field when the model supports thinking, intentionally
 // overwriting caller-provided values to honor suffix/default metadata priority.
-func applyReasoningEffortMetadata(payload []byte, metadata map[string]any, model, field string) []byte {
+func ApplyReasoningEffortMetadata(payload []byte, metadata map[string]any, model, field string, allowCompat bool) []byte {
 	if len(metadata) == 0 {
 		return payload
 	}
@@ -59,12 +59,30 @@ func applyReasoningEffortMetadata(payload []byte, metadata map[string]any, model
 	if baseModel == "" {
 		baseModel = model
 	}
-	if !util.ModelSupportsThinking(baseModel) && !util.IsOpenAICompatibilityModel(baseModel) {
+	if !util.ModelSupportsThinking(baseModel) && !allowCompat {
 		return payload
 	}
 	if effort, ok := util.ReasoningEffortFromMetadata(metadata); ok && effort != "" {
-		if updated, err := sjson.SetBytes(payload, field, effort); err == nil {
-			return updated
+		if util.ModelUsesThinkingLevels(baseModel) || allowCompat {
+			if updated, err := sjson.SetBytes(payload, field, effort); err == nil {
+				return updated
+			}
+		}
+	}
+	// Fallback: numeric thinking_budget suffix for level-based (OpenAI-style) models.
+	if util.ModelUsesThinkingLevels(baseModel) || allowCompat {
+		if budget, _, _, matched := util.ThinkingFromMetadata(metadata); matched && budget != nil {
+			if effort, ok := util.OpenAIThinkingBudgetToEffort(baseModel, *budget); ok && effort != "" {
+				if *budget == 0 && effort == "none" && util.ModelUsesThinkingLevels(baseModel) {
+					if _, supported := util.NormalizeReasoningEffortLevel(baseModel, effort); !supported {
+						return StripThinkingFields(payload, false)
+					}
+				}
+
+				if updated, err := sjson.SetBytes(payload, field, effort); err == nil {
+					return updated
+				}
+			}
 		}
 	}
 	return payload
@@ -220,37 +238,43 @@ func matchModelPattern(pattern, model string) bool {
 	return pi == len(pattern)
 }
 
-// normalizeThinkingConfig normalizes thinking-related fields in the payload
+// NormalizeThinkingConfig normalizes thinking-related fields in the payload
 // based on model capabilities. For models without thinking support, it strips
 // reasoning fields. For models with level-based thinking, it validates and
-// normalizes the reasoning effort level.
-func normalizeThinkingConfig(payload []byte, model string) []byte {
+// normalizes the reasoning effort level. For models with numeric budget thinking,
+// it strips the effort string fields.
+func NormalizeThinkingConfig(payload []byte, model string, allowCompat bool) []byte {
 	if len(payload) == 0 || model == "" {
 		return payload
 	}
 
 	if !util.ModelSupportsThinking(model) {
-		if util.IsOpenAICompatibilityModel(model) {
+		if allowCompat {
 			return payload
 		}
-		return stripThinkingFields(payload)
+		return StripThinkingFields(payload, false)
 	}
 
 	if util.ModelUsesThinkingLevels(model) {
-		return normalizeReasoningEffortLevel(payload, model)
+		return NormalizeReasoningEffortLevel(payload, model)
 	}
 
-	return payload
+	// Model supports thinking but uses numeric budgets, not levels.
+	// Strip effort string fields since they are not applicable.
+	return StripThinkingFields(payload, true)
 }
 
-// stripThinkingFields removes thinking-related fields from the payload for
-// models that do not support thinking.
-func stripThinkingFields(payload []byte) []byte {
+// StripThinkingFields removes thinking-related fields from the payload for
+// models that do not support thinking. If effortOnly is true, only removes
+// effort string fields (for models using numeric budgets).
+func StripThinkingFields(payload []byte, effortOnly bool) []byte {
 	fieldsToRemove := []string{
-		"reasoning",
 		"reasoning_effort",
 		"reasoning.effort",
 	}
+	if !effortOnly {
+		fieldsToRemove = append([]string{"reasoning"}, fieldsToRemove...)
+	}
 	out := payload
 	for _, field := range fieldsToRemove {
 		if gjson.GetBytes(out, field).Exists() {
@@ -260,9 +284,9 @@ func stripThinkingFields(payload []byte) []byte {
 	return out
 }
 
-// normalizeReasoningEffortLevel validates and normalizes the reasoning_effort
+// NormalizeReasoningEffortLevel validates and normalizes the reasoning_effort
 // or reasoning.effort field for level-based thinking models.
-func normalizeReasoningEffortLevel(payload []byte, model string) []byte {
+func NormalizeReasoningEffortLevel(payload []byte, model string) []byte {
 	out := payload
 
 	if effort := gjson.GetBytes(out, "reasoning_effort"); effort.Exists() {
@@ -280,10 +304,10 @@ func normalizeReasoningEffortLevel(payload []byte, model string) []byte {
 	return out
 }
 
-// validateThinkingConfig checks for unsupported reasoning levels on level-based models.
+// ValidateThinkingConfig checks for unsupported reasoning levels on level-based models.
 // Returns a statusErr with 400 when an unsupported level is supplied to avoid silently
 // downgrading requests.
-func validateThinkingConfig(payload []byte, model string) error {
+func ValidateThinkingConfig(payload []byte, model string) error {
 	if len(payload) == 0 || model == "" {
 		return nil
 	}

internal/runtime/executor/qwen_executor.go

@@ -51,13 +51,13 @@ func (e *QwenExecutor) Execute(ctx context.Context, auth *cliproxyauth.Auth, req
 	from := opts.SourceFormat
 	to := sdktranslator.FromString("openai")
 	body := sdktranslator.TranslateRequest(from, to, req.Model, bytes.Clone(req.Payload), false)
-	body = applyReasoningEffortMetadata(body, req.Metadata, req.Model, "reasoning_effort")
+	body = ApplyReasoningEffortMetadata(body, req.Metadata, req.Model, "reasoning_effort", false)
 	upstreamModel := util.ResolveOriginalModel(req.Model, req.Metadata)
 	if upstreamModel != "" {
 		body, _ = sjson.SetBytes(body, "model", upstreamModel)
 	}
-	body = normalizeThinkingConfig(body, upstreamModel)
-	if errValidate := validateThinkingConfig(body, upstreamModel); errValidate != nil {
+	body = NormalizeThinkingConfig(body, upstreamModel, false)
+	if errValidate := ValidateThinkingConfig(body, upstreamModel); errValidate != nil {
 		return resp, errValidate
 	}
 	body = applyPayloadConfig(e.cfg, req.Model, body)
@@ -131,13 +131,13 @@ func (e *QwenExecutor) ExecuteStream(ctx context.Context, auth *cliproxyauth.Aut
 	to := sdktranslator.FromString("openai")
 	body := sdktranslator.TranslateRequest(from, to, req.Model, bytes.Clone(req.Payload), true)
 
-	body = applyReasoningEffortMetadata(body, req.Metadata, req.Model, "reasoning_effort")
+	body = ApplyReasoningEffortMetadata(body, req.Metadata, req.Model, "reasoning_effort", false)
 	upstreamModel := util.ResolveOriginalModel(req.Model, req.Metadata)
 	if upstreamModel != "" {
 		body, _ = sjson.SetBytes(body, "model", upstreamModel)
 	}
-	body = normalizeThinkingConfig(body, upstreamModel)
-	if errValidate := validateThinkingConfig(body, upstreamModel); errValidate != nil {
+	body = NormalizeThinkingConfig(body, upstreamModel, false)
+	if errValidate := ValidateThinkingConfig(body, upstreamModel); errValidate != nil {
 		return nil, errValidate
 	}
 	toolsResult := gjson.GetBytes(body, "tools")

internal/translator/antigravity/gemini/antigravity_gemini_request.go

@@ -122,6 +122,38 @@ type FunctionCallGroup struct {
 	ResponsesNeeded int
 }
 
+// parseFunctionResponse attempts to unmarshal a function response part.
+// Falls back to gjson extraction if standard json.Unmarshal fails.
+func parseFunctionResponse(response gjson.Result) map[string]interface{} {
+	var responseMap map[string]interface{}
+	err := json.Unmarshal([]byte(response.Raw), &responseMap)
+	if err == nil {
+		return responseMap
+	}
+
+	log.Debugf("unmarshal function response failed, using fallback: %v", err)
+	funcResp := response.Get("functionResponse")
+	if funcResp.Exists() {
+		fr := map[string]interface{}{
+			"name": funcResp.Get("name").String(),
+			"response": map[string]interface{}{
+				"result": funcResp.Get("response").String(),
+			},
+		}
+		if id := funcResp.Get("id").String(); id != "" {
+			fr["id"] = id
+		}
+		return map[string]interface{}{"functionResponse": fr}
+	}
+
+	return map[string]interface{}{
+		"functionResponse": map[string]interface{}{
+			"name":     "unknown",
+			"response": map[string]interface{}{"result": response.String()},
+		},
+	}
+}
+
 // fixCLIToolResponse performs sophisticated tool response format conversion and grouping.
 // This function transforms the CLI tool response format by intelligently grouping function calls
 // with their corresponding responses, ensuring proper conversation flow and API compatibility.
@@ -180,13 +212,7 @@ func fixCLIToolResponse(input string) (string, error) {
 					// Create merged function response content
 					var responseParts []interface{}
 					for _, response := range groupResponses {
-						var responseMap map[string]interface{}
-						errUnmarshal := json.Unmarshal([]byte(response.Raw), &responseMap)
-						if errUnmarshal != nil {
-							log.Warnf("failed to unmarshal function response: %v\n", errUnmarshal)
-							continue
-						}
-						responseParts = append(responseParts, responseMap)
+						responseParts = append(responseParts, parseFunctionResponse(response))
 					}
 
 					if len(responseParts) > 0 {
@@ -265,13 +291,7 @@ func fixCLIToolResponse(input string) (string, error) {
 
 			var responseParts []interface{}
 			for _, response := range groupResponses {
-				var responseMap map[string]interface{}
-				errUnmarshal := json.Unmarshal([]byte(response.Raw), &responseMap)
-				if errUnmarshal != nil {
-					log.Warnf("failed to unmarshal function response: %v\n", errUnmarshal)
-					continue
-				}
-				responseParts = append(responseParts, responseMap)
+				responseParts = append(responseParts, parseFunctionResponse(response))
 			}
 
 			if len(responseParts) > 0 {

internal/translator/antigravity/openai/chat-completions/antigravity_openai_request.go

@@ -39,31 +39,13 @@ func ConvertOpenAIRequestToAntigravity(modelName string, inputRawJSON []byte, _
 	// Note: OpenAI official fields take precedence over extra_body.google.thinking_config
 	re := gjson.GetBytes(rawJSON, "reasoning_effort")
 	hasOfficialThinking := re.Exists()
-	if hasOfficialThinking && util.ModelSupportsThinking(modelName) {
-		switch re.String() {
-		case "none":
-			out, _ = sjson.DeleteBytes(out, "request.generationConfig.thinkingConfig.include_thoughts")
-			out, _ = sjson.SetBytes(out, "request.generationConfig.thinkingConfig.thinkingBudget", 0)
-		case "auto":
-			out, _ = sjson.SetBytes(out, "request.generationConfig.thinkingConfig.thinkingBudget", -1)
-			out, _ = sjson.SetBytes(out, "request.generationConfig.thinkingConfig.include_thoughts", true)
-		case "low":
-			out, _ = sjson.SetBytes(out, "request.generationConfig.thinkingConfig.thinkingBudget", 1024)
-			out, _ = sjson.SetBytes(out, "request.generationConfig.thinkingConfig.include_thoughts", true)
-		case "medium":
-			out, _ = sjson.SetBytes(out, "request.generationConfig.thinkingConfig.thinkingBudget", 8192)
-			out, _ = sjson.SetBytes(out, "request.generationConfig.thinkingConfig.include_thoughts", true)
-		case "high":
-			out, _ = sjson.SetBytes(out, "request.generationConfig.thinkingConfig.thinkingBudget", 32768)
-			out, _ = sjson.SetBytes(out, "request.generationConfig.thinkingConfig.include_thoughts", true)
-		default:
-			out, _ = sjson.SetBytes(out, "request.generationConfig.thinkingConfig.thinkingBudget", -1)
-			out, _ = sjson.SetBytes(out, "request.generationConfig.thinkingConfig.include_thoughts", true)
-		}
+	if hasOfficialThinking && util.ModelSupportsThinking(modelName) && !util.ModelUsesThinkingLevels(modelName) {
+		out = util.ApplyReasoningEffortToGeminiCLI(out, re.String())
 	}
 
 	// Cherry Studio extension extra_body.google.thinking_config (effective only when official fields are absent)
-	if !hasOfficialThinking && util.ModelSupportsThinking(modelName) {
+	// Only apply for models that use numeric budgets, not discrete levels.
+	if !hasOfficialThinking && util.ModelSupportsThinking(modelName) && !util.ModelUsesThinkingLevels(modelName) {
 		if tc := gjson.GetBytes(rawJSON, "extra_body.google.thinking_config"); tc.Exists() && tc.IsObject() {
 			var setBudget bool
 			var budget int

internal/translator/claude/gemini/claude_gemini_request.go

@@ -114,14 +114,16 @@ func ConvertGeminiRequestToClaude(modelName string, inputRawJSON []byte, stream
 			}
 		}
 		// Include thoughts configuration for reasoning process visibility
-		if thinkingConfig := genConfig.Get("thinkingConfig"); thinkingConfig.Exists() && thinkingConfig.IsObject() {
-			if includeThoughts := thinkingConfig.Get("include_thoughts"); includeThoughts.Exists() {
-				if includeThoughts.Type == gjson.True {
-					out, _ = sjson.Set(out, "thinking.type", "enabled")
-					if thinkingBudget := thinkingConfig.Get("thinkingBudget"); thinkingBudget.Exists() {
-						out, _ = sjson.Set(out, "thinking.budget_tokens", thinkingBudget.Int())
-					}
-				}
+		// Only apply for models that support thinking and use numeric budgets, not discrete levels.
+		if thinkingConfig := genConfig.Get("thinkingConfig"); thinkingConfig.Exists() && thinkingConfig.IsObject() && util.ModelSupportsThinking(modelName) && !util.ModelUsesThinkingLevels(modelName) {
+			// Check for thinkingBudget first - if present, enable thinking with budget
+			if thinkingBudget := thinkingConfig.Get("thinkingBudget"); thinkingBudget.Exists() && thinkingBudget.Int() > 0 {
+				out, _ = sjson.Set(out, "thinking.type", "enabled")
+				normalizedBudget := util.NormalizeThinkingBudget(modelName, int(thinkingBudget.Int()))
+				out, _ = sjson.Set(out, "thinking.budget_tokens", normalizedBudget)
+			} else if includeThoughts := thinkingConfig.Get("include_thoughts"); includeThoughts.Exists() && includeThoughts.Type == gjson.True {
+				// Fallback to include_thoughts if no budget specified
+				out, _ = sjson.Set(out, "thinking.type", "enabled")
 			}
 		}
 	}

internal/translator/claude/openai/chat-completions/claude_openai_request.go

@@ -16,6 +16,7 @@ import (
 	"strings"
 
 	"github.com/google/uuid"
+	"github.com/router-for-me/CLIProxyAPI/v6/internal/util"
 	"github.com/tidwall/gjson"
 	"github.com/tidwall/sjson"
 )
@@ -65,18 +66,23 @@ func ConvertOpenAIRequestToClaude(modelName string, inputRawJSON []byte, stream
 
 	root := gjson.ParseBytes(rawJSON)
 
-	if v := root.Get("reasoning_effort"); v.Exists() {
-		out, _ = sjson.Set(out, "thinking.type", "enabled")
-
-		switch v.String() {
-		case "none":
-			out, _ = sjson.Set(out, "thinking.type", "disabled")
-		case "low":
-			out, _ = sjson.Set(out, "thinking.budget_tokens", 1024)
-		case "medium":
-			out, _ = sjson.Set(out, "thinking.budget_tokens", 8192)
-		case "high":
-			out, _ = sjson.Set(out, "thinking.budget_tokens", 24576)
+	if v := root.Get("reasoning_effort"); v.Exists() && util.ModelSupportsThinking(modelName) && !util.ModelUsesThinkingLevels(modelName) {
+		effort := strings.ToLower(strings.TrimSpace(v.String()))
+		if effort != "" {
+			budget, ok := util.ThinkingEffortToBudget(modelName, effort)
+			if ok {
+				switch budget {
+				case 0:
+					out, _ = sjson.Set(out, "thinking.type", "disabled")
+				case -1:
+					out, _ = sjson.Set(out, "thinking.type", "enabled")
+				default:
+					if budget > 0 {
+						out, _ = sjson.Set(out, "thinking.type", "enabled")
+						out, _ = sjson.Set(out, "thinking.budget_tokens", budget)
+					}
+				}
+			}
 		}
 	}
 

internal/translator/claude/openai/responses/claude_openai-responses_request.go

@@ -10,6 +10,7 @@ import (
 	"strings"
 
 	"github.com/google/uuid"
+	"github.com/router-for-me/CLIProxyAPI/v6/internal/util"
 	"github.com/tidwall/gjson"
 	"github.com/tidwall/sjson"
 )
@@ -52,20 +53,23 @@ func ConvertOpenAIResponsesRequestToClaude(modelName string, inputRawJSON []byte
 
 	root := gjson.ParseBytes(rawJSON)
 
-	if v := root.Get("reasoning.effort"); v.Exists() {
-		out, _ = sjson.Set(out, "thinking.type", "enabled")
-
-		switch v.String() {
-		case "none":
-			out, _ = sjson.Set(out, "thinking.type", "disabled")
-		case "minimal":
-			out, _ = sjson.Set(out, "thinking.budget_tokens", 1024)
-		case "low":
-			out, _ = sjson.Set(out, "thinking.budget_tokens", 4096)
-		case "medium":
-			out, _ = sjson.Set(out, "thinking.budget_tokens", 8192)
-		case "high":
-			out, _ = sjson.Set(out, "thinking.budget_tokens", 24576)
+	if v := root.Get("reasoning.effort"); v.Exists() && util.ModelSupportsThinking(modelName) && !util.ModelUsesThinkingLevels(modelName) {
+		effort := strings.ToLower(strings.TrimSpace(v.String()))
+		if effort != "" {
+			budget, ok := util.ThinkingEffortToBudget(modelName, effort)
+			if ok {
+				switch budget {
+				case 0:
+					out, _ = sjson.Set(out, "thinking.type", "disabled")
+				case -1:
+					out, _ = sjson.Set(out, "thinking.type", "enabled")
+				default:
+					if budget > 0 {
+						out, _ = sjson.Set(out, "thinking.type", "enabled")
+						out, _ = sjson.Set(out, "thinking.budget_tokens", budget)
+					}
+				}
+			}
 		}
 	}
 

internal/translator/codex/claude/codex_claude_request.go

@@ -12,6 +12,7 @@ import (
 	"strings"
 
 	"github.com/router-for-me/CLIProxyAPI/v6/internal/misc"
+	"github.com/router-for-me/CLIProxyAPI/v6/internal/util"
 	"github.com/tidwall/gjson"
 	"github.com/tidwall/sjson"
 )
@@ -214,7 +215,22 @@ func ConvertClaudeRequestToCodex(modelName string, inputRawJSON []byte, _ bool)
 
 	// Add additional configuration parameters for the Codex API.
 	template, _ = sjson.Set(template, "parallel_tool_calls", true)
-	template, _ = sjson.Set(template, "reasoning.effort", "medium")
+
+	// Convert thinking.budget_tokens to reasoning.effort for level-based models
+	reasoningEffort := "medium" // default
+	if thinking := rootResult.Get("thinking"); thinking.Exists() && thinking.IsObject() {
+		if thinking.Get("type").String() == "enabled" {
+			if util.ModelUsesThinkingLevels(modelName) {
+				if budgetTokens := thinking.Get("budget_tokens"); budgetTokens.Exists() {
+					budget := int(budgetTokens.Int())
+					if effort, ok := util.OpenAIThinkingBudgetToEffort(modelName, budget); ok && effort != "" {
+						reasoningEffort = effort
+					}
+				}
+			}
+		}
+	}
+	template, _ = sjson.Set(template, "reasoning.effort", reasoningEffort)
 	template, _ = sjson.Set(template, "reasoning.summary", "auto")
 	template, _ = sjson.Set(template, "stream", true)
 	template, _ = sjson.Set(template, "store", false)

internal/translator/codex/gemini/codex_gemini_request.go

@@ -245,7 +245,22 @@ func ConvertGeminiRequestToCodex(modelName string, inputRawJSON []byte, _ bool)
 
 	// Fixed flags aligning with Codex expectations
 	out, _ = sjson.Set(out, "parallel_tool_calls", true)
-	out, _ = sjson.Set(out, "reasoning.effort", "medium")
+
+	// Convert thinkingBudget to reasoning.effort for level-based models
+	reasoningEffort := "medium" // default
+	if genConfig := root.Get("generationConfig"); genConfig.Exists() {
+		if thinkingConfig := genConfig.Get("thinkingConfig"); thinkingConfig.Exists() && thinkingConfig.IsObject() {
+			if util.ModelUsesThinkingLevels(modelName) {
+				if thinkingBudget := thinkingConfig.Get("thinkingBudget"); thinkingBudget.Exists() {
+					budget := int(thinkingBudget.Int())
+					if effort, ok := util.OpenAIThinkingBudgetToEffort(modelName, budget); ok && effort != "" {
+						reasoningEffort = effort
+					}
+				}
+			}
+		}
+	}
+	out, _ = sjson.Set(out, "reasoning.effort", reasoningEffort)
 	out, _ = sjson.Set(out, "reasoning.summary", "auto")
 	out, _ = sjson.Set(out, "stream", true)
 	out, _ = sjson.Set(out, "store", false)

internal/translator/gemini-cli/openai/chat-completions/gemini-cli_openai_request.go

@@ -39,31 +39,13 @@ func ConvertOpenAIRequestToGeminiCLI(modelName string, inputRawJSON []byte, _ bo
 	// Note: OpenAI official fields take precedence over extra_body.google.thinking_config
 	re := gjson.GetBytes(rawJSON, "reasoning_effort")
 	hasOfficialThinking := re.Exists()
-	if hasOfficialThinking && util.ModelSupportsThinking(modelName) {
-		switch re.String() {
-		case "none":
-			out, _ = sjson.DeleteBytes(out, "request.generationConfig.thinkingConfig.include_thoughts")
-			out, _ = sjson.SetBytes(out, "request.generationConfig.thinkingConfig.thinkingBudget", 0)
-		case "auto":
-			out, _ = sjson.SetBytes(out, "request.generationConfig.thinkingConfig.thinkingBudget", -1)
-			out, _ = sjson.SetBytes(out, "request.generationConfig.thinkingConfig.include_thoughts", true)
-		case "low":
-			out, _ = sjson.SetBytes(out, "request.generationConfig.thinkingConfig.thinkingBudget", 1024)
-			out, _ = sjson.SetBytes(out, "request.generationConfig.thinkingConfig.include_thoughts", true)
-		case "medium":
-			out, _ = sjson.SetBytes(out, "request.generationConfig.thinkingConfig.thinkingBudget", 8192)
-			out, _ = sjson.SetBytes(out, "request.generationConfig.thinkingConfig.include_thoughts", true)
-		case "high":
-			out, _ = sjson.SetBytes(out, "request.generationConfig.thinkingConfig.thinkingBudget", 32768)
-			out, _ = sjson.SetBytes(out, "request.generationConfig.thinkingConfig.include_thoughts", true)
-		default:
-			out, _ = sjson.SetBytes(out, "request.generationConfig.thinkingConfig.thinkingBudget", -1)
-			out, _ = sjson.SetBytes(out, "request.generationConfig.thinkingConfig.include_thoughts", true)
-		}
+	if hasOfficialThinking && util.ModelSupportsThinking(modelName) && !util.ModelUsesThinkingLevels(modelName) {
+		out = util.ApplyReasoningEffortToGeminiCLI(out, re.String())
 	}
 
 	// Cherry Studio extension extra_body.google.thinking_config (effective only when official fields are absent)
-	if !hasOfficialThinking && util.ModelSupportsThinking(modelName) {
+	// Only apply for models that use numeric budgets, not discrete levels.
+	if !hasOfficialThinking && util.ModelSupportsThinking(modelName) && !util.ModelUsesThinkingLevels(modelName) {
 		if tc := gjson.GetBytes(rawJSON, "extra_body.google.thinking_config"); tc.Exists() && tc.IsObject() {
 			var setBudget bool
 			var budget int

internal/translator/gemini/claude/gemini_claude_request.go

@@ -154,7 +154,8 @@ func ConvertClaudeRequestToGemini(modelName string, inputRawJSON []byte, _ bool)
 	}
 
 	// Map Anthropic thinking -> Gemini thinkingBudget/include_thoughts when enabled
-	if t := gjson.GetBytes(rawJSON, "thinking"); t.Exists() && t.IsObject() && util.ModelSupportsThinking(modelName) {
+	// Only apply for models that use numeric budgets, not discrete levels.
+	if t := gjson.GetBytes(rawJSON, "thinking"); t.Exists() && t.IsObject() && util.ModelSupportsThinking(modelName) && !util.ModelUsesThinkingLevels(modelName) {
 		if t.Get("type").String() == "enabled" {
 			if b := t.Get("budget_tokens"); b.Exists() && b.Type == gjson.Number {
 				budget := int(b.Int())

internal/translator/gemini/openai/chat-completions/gemini_openai_request.go

@@ -37,33 +37,17 @@ func ConvertOpenAIRequestToGemini(modelName string, inputRawJSON []byte, _ bool)
 
 	// Reasoning effort -> thinkingBudget/include_thoughts
 	// Note: OpenAI official fields take precedence over extra_body.google.thinking_config
+	// Only convert for models that use numeric budgets (not discrete levels) to avoid
+	// incorrectly applying thinkingBudget for level-based models like gpt-5.
 	re := gjson.GetBytes(rawJSON, "reasoning_effort")
 	hasOfficialThinking := re.Exists()
-	if hasOfficialThinking && util.ModelSupportsThinking(modelName) {
-		switch re.String() {
-		case "none":
-			out, _ = sjson.DeleteBytes(out, "generationConfig.thinkingConfig.include_thoughts")
-			out, _ = sjson.SetBytes(out, "generationConfig.thinkingConfig.thinkingBudget", 0)
-		case "auto":
-			out, _ = sjson.SetBytes(out, "generationConfig.thinkingConfig.thinkingBudget", -1)
-			out, _ = sjson.SetBytes(out, "generationConfig.thinkingConfig.include_thoughts", true)
-		case "low":
-			out, _ = sjson.SetBytes(out, "generationConfig.thinkingConfig.thinkingBudget", 1024)
-			out, _ = sjson.SetBytes(out, "generationConfig.thinkingConfig.include_thoughts", true)
-		case "medium":
-			out, _ = sjson.SetBytes(out, "generationConfig.thinkingConfig.thinkingBudget", 8192)
-			out, _ = sjson.SetBytes(out, "generationConfig.thinkingConfig.include_thoughts", true)
-		case "high":
-			out, _ = sjson.SetBytes(out, "generationConfig.thinkingConfig.thinkingBudget", 32768)
-			out, _ = sjson.SetBytes(out, "generationConfig.thinkingConfig.include_thoughts", true)
-		default:
-			out, _ = sjson.SetBytes(out, "generationConfig.thinkingConfig.thinkingBudget", -1)
-			out, _ = sjson.SetBytes(out, "generationConfig.thinkingConfig.include_thoughts", true)
-		}
+	if hasOfficialThinking && util.ModelSupportsThinking(modelName) && !util.ModelUsesThinkingLevels(modelName) {
+		out = util.ApplyReasoningEffortToGemini(out, re.String())
 	}
 
 	// Cherry Studio extension extra_body.google.thinking_config (effective only when official fields are absent)
-	if !hasOfficialThinking && util.ModelSupportsThinking(modelName) {
+	// Only apply for models that use numeric budgets, not discrete levels.
+	if !hasOfficialThinking && util.ModelSupportsThinking(modelName) && !util.ModelUsesThinkingLevels(modelName) {
 		if tc := gjson.GetBytes(rawJSON, "extra_body.google.thinking_config"); tc.Exists() && tc.IsObject() {
 			var setBudget bool
 			var budget int

internal/translator/gemini/openai/responses/gemini_openai-responses_request.go

@@ -389,36 +389,16 @@ func ConvertOpenAIResponsesRequestToGemini(modelName string, inputRawJSON []byte
 	}
 
 	// OpenAI official reasoning fields take precedence
+	// Only convert for models that use numeric budgets (not discrete levels).
 	hasOfficialThinking := root.Get("reasoning.effort").Exists()
-	if hasOfficialThinking && util.ModelSupportsThinking(modelName) {
+	if hasOfficialThinking && util.ModelSupportsThinking(modelName) && !util.ModelUsesThinkingLevels(modelName) {
 		reasoningEffort := root.Get("reasoning.effort")
-		switch reasoningEffort.String() {
-		case "none":
-			out, _ = sjson.Set(out, "generationConfig.thinkingConfig.include_thoughts", false)
-			out, _ = sjson.Set(out, "generationConfig.thinkingConfig.thinkingBudget", 0)
-		case "auto":
-			out, _ = sjson.Set(out, "generationConfig.thinkingConfig.thinkingBudget", -1)
-			out, _ = sjson.Set(out, "generationConfig.thinkingConfig.include_thoughts", true)
-		case "minimal":
-			out, _ = sjson.Set(out, "generationConfig.thinkingConfig.thinkingBudget", 1024)
-			out, _ = sjson.Set(out, "generationConfig.thinkingConfig.include_thoughts", true)
-		case "low":
-			out, _ = sjson.Set(out, "generationConfig.thinkingConfig.thinkingBudget", 4096)
-			out, _ = sjson.Set(out, "generationConfig.thinkingConfig.include_thoughts", true)
-		case "medium":
-			out, _ = sjson.Set(out, "generationConfig.thinkingConfig.thinkingBudget", 8192)
-			out, _ = sjson.Set(out, "generationConfig.thinkingConfig.include_thoughts", true)
-		case "high":
-			out, _ = sjson.Set(out, "generationConfig.thinkingConfig.thinkingBudget", 32768)
-			out, _ = sjson.Set(out, "generationConfig.thinkingConfig.include_thoughts", true)
-		default:
-			out, _ = sjson.Set(out, "generationConfig.thinkingConfig.thinkingBudget", -1)
-			out, _ = sjson.Set(out, "generationConfig.thinkingConfig.include_thoughts", true)
-		}
+		out = string(util.ApplyReasoningEffortToGemini([]byte(out), reasoningEffort.String()))
 	}
 
 	// Cherry Studio extension (applies only when official fields are missing)
-	if !hasOfficialThinking && util.ModelSupportsThinking(modelName) {
+	// Only apply for models that use numeric budgets, not discrete levels.
+	if !hasOfficialThinking && util.ModelSupportsThinking(modelName) && !util.ModelUsesThinkingLevels(modelName) {
 		if tc := root.Get("extra_body.google.thinking_config"); tc.Exists() && tc.IsObject() {
 			var setBudget bool
 			var budget int

internal/translator/init.go

@@ -35,5 +35,5 @@ import (
 	_ "github.com/router-for-me/CLIProxyAPI/v6/internal/translator/antigravity/openai/responses"
 
 	_ "github.com/router-for-me/CLIProxyAPI/v6/internal/translator/kiro/claude"
-	_ "github.com/router-for-me/CLIProxyAPI/v6/internal/translator/kiro/openai/chat-completions"
+	_ "github.com/router-for-me/CLIProxyAPI/v6/internal/translator/kiro/openai"
 )

internal/translator/kiro/claude/init.go

@@ -1,3 +1,4 @@
+// Package claude provides translation between Kiro and Claude formats.
 package claude
 
 import (
@@ -12,8 +13,8 @@ func init() {
 		Kiro,
 		ConvertClaudeRequestToKiro,
 		interfaces.TranslateResponse{
-			Stream:    ConvertKiroResponseToClaude,
-			NonStream: ConvertKiroResponseToClaudeNonStream,
+			Stream:    ConvertKiroStreamToClaude,
+			NonStream: ConvertKiroNonStreamToClaude,
 		},
 	)
 }

internal/translator/kiro/claude/kiro_claude.go

@@ -1,27 +1,21 @@
 // Package claude provides translation between Kiro and Claude formats.
 // Since Kiro executor generates Claude-compatible SSE format internally (with event: prefix),
-// translations are pass-through.
+// translations are pass-through for streaming, but responses need proper formatting.
 package claude
 
 import (
-	"bytes"
 	"context"
 )
 
-// ConvertClaudeRequestToKiro converts Claude request to Kiro format.
-// Since Kiro uses Claude format internally, this is mostly a pass-through.
-func ConvertClaudeRequestToKiro(modelName string, inputRawJSON []byte, stream bool) []byte {
-	return bytes.Clone(inputRawJSON)
-}
-
-// ConvertKiroResponseToClaude converts Kiro streaming response to Claude format.
+// ConvertKiroStreamToClaude converts Kiro streaming response to Claude format.
 // Kiro executor already generates complete SSE format with "event:" prefix,
 // so this is a simple pass-through.
-func ConvertKiroResponseToClaude(ctx context.Context, model string, originalRequest, request, rawResponse []byte, param *any) []string {
+func ConvertKiroStreamToClaude(ctx context.Context, model string, originalRequest, request, rawResponse []byte, param *any) []string {
 	return []string{string(rawResponse)}
 }
 
-// ConvertKiroResponseToClaudeNonStream converts Kiro non-streaming response to Claude format.
-func ConvertKiroResponseToClaudeNonStream(ctx context.Context, model string, originalRequest, request, rawResponse []byte, param *any) string {
+// ConvertKiroNonStreamToClaude converts Kiro non-streaming response to Claude format.
+// The response is already in Claude format, so this is a pass-through.
+func ConvertKiroNonStreamToClaude(ctx context.Context, model string, originalRequest, request, rawResponse []byte, param *any) string {
 	return string(rawResponse)
 }

internal/translator/kiro/claude/kiro_claude_request.go

@@ -0,0 +1,774 @@
+// Package claude provides request translation functionality for Claude API to Kiro format.
+// It handles parsing and transforming Claude API requests into the Kiro/Amazon Q API format,
+// extracting model information, system instructions, message contents, and tool declarations.
+package claude
+
+import (
+	"encoding/json"
+	"fmt"
+	"strings"
+	"time"
+	"unicode/utf8"
+
+	"github.com/google/uuid"
+	kirocommon "github.com/router-for-me/CLIProxyAPI/v6/internal/translator/kiro/common"
+	log "github.com/sirupsen/logrus"
+	"github.com/tidwall/gjson"
+)
+
+
+// Kiro API request structs - field order determines JSON key order
+
+// KiroPayload is the top-level request structure for Kiro API
+type KiroPayload struct {
+	ConversationState KiroConversationState `json:"conversationState"`
+	ProfileArn        string                `json:"profileArn,omitempty"`
+	InferenceConfig   *KiroInferenceConfig  `json:"inferenceConfig,omitempty"`
+}
+
+// KiroInferenceConfig contains inference parameters for the Kiro API.
+type KiroInferenceConfig struct {
+	MaxTokens   int     `json:"maxTokens,omitempty"`
+	Temperature float64 `json:"temperature,omitempty"`
+	TopP        float64 `json:"topP,omitempty"`
+}
+
+// KiroConversationState holds the conversation context
+type KiroConversationState struct {
+	ChatTriggerType string               `json:"chatTriggerType"` // Required: "MANUAL" - must be first field
+	ConversationID  string               `json:"conversationId"`
+	CurrentMessage  KiroCurrentMessage   `json:"currentMessage"`
+	History         []KiroHistoryMessage `json:"history,omitempty"`
+}
+
+// KiroCurrentMessage wraps the current user message
+type KiroCurrentMessage struct {
+	UserInputMessage KiroUserInputMessage `json:"userInputMessage"`
+}
+
+// KiroHistoryMessage represents a message in the conversation history
+type KiroHistoryMessage struct {
+	UserInputMessage         *KiroUserInputMessage         `json:"userInputMessage,omitempty"`
+	AssistantResponseMessage *KiroAssistantResponseMessage `json:"assistantResponseMessage,omitempty"`
+}
+
+// KiroImage represents an image in Kiro API format
+type KiroImage struct {
+	Format string          `json:"format"`
+	Source KiroImageSource `json:"source"`
+}
+
+// KiroImageSource contains the image data
+type KiroImageSource struct {
+	Bytes string `json:"bytes"` // base64 encoded image data
+}
+
+// KiroUserInputMessage represents a user message
+type KiroUserInputMessage struct {
+	Content                 string                       `json:"content"`
+	ModelID                 string                       `json:"modelId"`
+	Origin                  string                       `json:"origin"`
+	Images                  []KiroImage                  `json:"images,omitempty"`
+	UserInputMessageContext *KiroUserInputMessageContext `json:"userInputMessageContext,omitempty"`
+}
+
+// KiroUserInputMessageContext contains tool-related context
+type KiroUserInputMessageContext struct {
+	ToolResults []KiroToolResult  `json:"toolResults,omitempty"`
+	Tools       []KiroToolWrapper `json:"tools,omitempty"`
+}
+
+// KiroToolResult represents a tool execution result
+type KiroToolResult struct {
+	Content   []KiroTextContent `json:"content"`
+	Status    string            `json:"status"`
+	ToolUseID string            `json:"toolUseId"`
+}
+
+// KiroTextContent represents text content
+type KiroTextContent struct {
+	Text string `json:"text"`
+}
+
+// KiroToolWrapper wraps a tool specification
+type KiroToolWrapper struct {
+	ToolSpecification KiroToolSpecification `json:"toolSpecification"`
+}
+
+// KiroToolSpecification defines a tool's schema
+type KiroToolSpecification struct {
+	Name        string          `json:"name"`
+	Description string          `json:"description"`
+	InputSchema KiroInputSchema `json:"inputSchema"`
+}
+
+// KiroInputSchema wraps the JSON schema for tool input
+type KiroInputSchema struct {
+	JSON interface{} `json:"json"`
+}
+
+// KiroAssistantResponseMessage represents an assistant message
+type KiroAssistantResponseMessage struct {
+	Content  string        `json:"content"`
+	ToolUses []KiroToolUse `json:"toolUses,omitempty"`
+}
+
+// KiroToolUse represents a tool invocation by the assistant
+type KiroToolUse struct {
+	ToolUseID string                 `json:"toolUseId"`
+	Name      string                 `json:"name"`
+	Input     map[string]interface{} `json:"input"`
+}
+
+// ConvertClaudeRequestToKiro converts a Claude API request to Kiro format.
+// This is the main entry point for request translation.
+func ConvertClaudeRequestToKiro(modelName string, inputRawJSON []byte, stream bool) []byte {
+	// For Kiro, we pass through the Claude format since buildKiroPayload
+	// expects Claude format and does the conversion internally.
+	// The actual conversion happens in the executor when building the HTTP request.
+	return inputRawJSON
+}
+
+// BuildKiroPayload constructs the Kiro API request payload from Claude format.
+// Supports tool calling - tools are passed via userInputMessageContext.
+// origin parameter determines which quota to use: "CLI" for Amazon Q, "AI_EDITOR" for Kiro IDE.
+// isAgentic parameter enables chunked write optimization prompt for -agentic model variants.
+// isChatOnly parameter disables tool calling for -chat model variants (pure conversation mode).
+// Supports thinking mode - when Claude API thinking parameter is present, injects thinkingHint.
+// Returns the payload and a boolean indicating whether thinking mode was injected.
+func BuildKiroPayload(claudeBody []byte, modelID, profileArn, origin string, isAgentic, isChatOnly bool) ([]byte, bool) {
+	// Extract max_tokens for potential use in inferenceConfig
+	// Handle -1 as "use maximum" (Kiro max output is ~32000 tokens)
+	const kiroMaxOutputTokens = 32000
+	var maxTokens int64
+	if mt := gjson.GetBytes(claudeBody, "max_tokens"); mt.Exists() {
+		maxTokens = mt.Int()
+		if maxTokens == -1 {
+			maxTokens = kiroMaxOutputTokens
+			log.Debugf("kiro: max_tokens=-1 converted to %d", kiroMaxOutputTokens)
+		}
+	}
+
+	// Extract temperature if specified
+	var temperature float64
+	var hasTemperature bool
+	if temp := gjson.GetBytes(claudeBody, "temperature"); temp.Exists() {
+		temperature = temp.Float()
+		hasTemperature = true
+	}
+
+	// Extract top_p if specified
+	var topP float64
+	var hasTopP bool
+	if tp := gjson.GetBytes(claudeBody, "top_p"); tp.Exists() {
+		topP = tp.Float()
+		hasTopP = true
+		log.Debugf("kiro: extracted top_p: %.2f", topP)
+	}
+
+	// Normalize origin value for Kiro API compatibility
+	origin = normalizeOrigin(origin)
+	log.Debugf("kiro: normalized origin value: %s", origin)
+
+	messages := gjson.GetBytes(claudeBody, "messages")
+
+	// For chat-only mode, don't include tools
+	var tools gjson.Result
+	if !isChatOnly {
+		tools = gjson.GetBytes(claudeBody, "tools")
+	}
+
+	// Extract system prompt
+	systemPrompt := extractSystemPrompt(claudeBody)
+
+	// Check for thinking mode using the comprehensive IsThinkingEnabled function
+	// This supports Claude API format, OpenAI reasoning_effort, and AMP/Cursor format
+	thinkingEnabled := IsThinkingEnabled(claudeBody)
+	_, budgetTokens := checkThinkingMode(claudeBody) // Get budget tokens from Claude format if available
+	if budgetTokens <= 0 {
+		// Calculate budgetTokens based on max_tokens if available
+		// Use 50% of max_tokens for thinking, with min 8000 and max 24000
+		if maxTokens > 0 {
+			budgetTokens = maxTokens / 2
+			if budgetTokens < 8000 {
+				budgetTokens = 8000
+			}
+			if budgetTokens > 24000 {
+				budgetTokens = 24000
+			}
+			log.Debugf("kiro: budgetTokens calculated from max_tokens: %d (max_tokens=%d)", budgetTokens, maxTokens)
+		} else {
+			budgetTokens = 16000 // Default budget tokens
+		}
+	}
+
+	// Inject timestamp context
+	timestamp := time.Now().Format("2006-01-02 15:04:05 MST")
+	timestampContext := fmt.Sprintf("[Context: Current time is %s]", timestamp)
+	if systemPrompt != "" {
+		systemPrompt = timestampContext + "\n\n" + systemPrompt
+	} else {
+		systemPrompt = timestampContext
+	}
+	log.Debugf("kiro: injected timestamp context: %s", timestamp)
+
+	// Inject agentic optimization prompt for -agentic model variants
+	if isAgentic {
+		if systemPrompt != "" {
+			systemPrompt += "\n"
+		}
+		systemPrompt += kirocommon.KiroAgenticSystemPrompt
+	}
+
+	// Handle tool_choice parameter - Kiro doesn't support it natively, so we inject system prompt hints
+	// Claude tool_choice values: {"type": "auto/any/tool", "name": "..."}
+	toolChoiceHint := extractClaudeToolChoiceHint(claudeBody)
+	if toolChoiceHint != "" {
+		if systemPrompt != "" {
+			systemPrompt += "\n"
+		}
+		systemPrompt += toolChoiceHint
+		log.Debugf("kiro: injected tool_choice hint into system prompt")
+	}
+
+	// Inject thinking hint when thinking mode is enabled
+	if thinkingEnabled {
+		if systemPrompt != "" {
+			systemPrompt += "\n"
+		}
+		dynamicThinkingHint := fmt.Sprintf("<thinking_mode>interleaved</thinking_mode><max_thinking_length>%d</max_thinking_length>", budgetTokens)
+		systemPrompt += dynamicThinkingHint
+		log.Debugf("kiro: injected dynamic thinking hint into system prompt, max_thinking_length: %d", budgetTokens)
+	}
+
+	// Convert Claude tools to Kiro format
+	kiroTools := convertClaudeToolsToKiro(tools)
+
+	// Process messages and build history
+	history, currentUserMsg, currentToolResults := processMessages(messages, modelID, origin)
+
+	// Build content with system prompt
+	if currentUserMsg != nil {
+		currentUserMsg.Content = buildFinalContent(currentUserMsg.Content, systemPrompt, currentToolResults)
+
+		// Deduplicate currentToolResults
+		currentToolResults = deduplicateToolResults(currentToolResults)
+
+		// Build userInputMessageContext with tools and tool results
+		if len(kiroTools) > 0 || len(currentToolResults) > 0 {
+			currentUserMsg.UserInputMessageContext = &KiroUserInputMessageContext{
+				Tools:       kiroTools,
+				ToolResults: currentToolResults,
+			}
+		}
+	}
+
+	// Build payload
+	var currentMessage KiroCurrentMessage
+	if currentUserMsg != nil {
+		currentMessage = KiroCurrentMessage{UserInputMessage: *currentUserMsg}
+	} else {
+		fallbackContent := ""
+		if systemPrompt != "" {
+			fallbackContent = "--- SYSTEM PROMPT ---\n" + systemPrompt + "\n--- END SYSTEM PROMPT ---\n"
+		}
+		currentMessage = KiroCurrentMessage{UserInputMessage: KiroUserInputMessage{
+			Content: fallbackContent,
+			ModelID: modelID,
+			Origin:  origin,
+		}}
+	}
+
+	// Build inferenceConfig if we have any inference parameters
+	var inferenceConfig *KiroInferenceConfig
+	if maxTokens > 0 || hasTemperature || hasTopP {
+		inferenceConfig = &KiroInferenceConfig{}
+		if maxTokens > 0 {
+			inferenceConfig.MaxTokens = int(maxTokens)
+		}
+		if hasTemperature {
+			inferenceConfig.Temperature = temperature
+		}
+		if hasTopP {
+			inferenceConfig.TopP = topP
+		}
+	}
+
+	payload := KiroPayload{
+		ConversationState: KiroConversationState{
+			ChatTriggerType: "MANUAL",
+			ConversationID:  uuid.New().String(),
+			CurrentMessage:  currentMessage,
+			History:         history,
+		},
+		ProfileArn:      profileArn,
+		InferenceConfig: inferenceConfig,
+	}
+
+	result, err := json.Marshal(payload)
+	if err != nil {
+		log.Debugf("kiro: failed to marshal payload: %v", err)
+		return nil, false
+	}
+
+	return result, thinkingEnabled
+}
+
+// normalizeOrigin normalizes origin value for Kiro API compatibility
+func normalizeOrigin(origin string) string {
+	switch origin {
+	case "KIRO_CLI":
+		return "CLI"
+	case "KIRO_AI_EDITOR":
+		return "AI_EDITOR"
+	case "AMAZON_Q":
+		return "CLI"
+	case "KIRO_IDE":
+		return "AI_EDITOR"
+	default:
+		return origin
+	}
+}
+
+// extractSystemPrompt extracts system prompt from Claude request
+func extractSystemPrompt(claudeBody []byte) string {
+	systemField := gjson.GetBytes(claudeBody, "system")
+	if systemField.IsArray() {
+		var sb strings.Builder
+		for _, block := range systemField.Array() {
+			if block.Get("type").String() == "text" {
+				sb.WriteString(block.Get("text").String())
+			} else if block.Type == gjson.String {
+				sb.WriteString(block.String())
+			}
+		}
+		return sb.String()
+	}
+	return systemField.String()
+}
+
+// checkThinkingMode checks if thinking mode is enabled in the Claude request
+func checkThinkingMode(claudeBody []byte) (bool, int64) {
+	thinkingEnabled := false
+	var budgetTokens int64 = 16000
+
+	thinkingField := gjson.GetBytes(claudeBody, "thinking")
+	if thinkingField.Exists() {
+		thinkingType := thinkingField.Get("type").String()
+		if thinkingType == "enabled" {
+			thinkingEnabled = true
+			if bt := thinkingField.Get("budget_tokens"); bt.Exists() {
+				budgetTokens = bt.Int()
+				if budgetTokens <= 0 {
+					thinkingEnabled = false
+					log.Debugf("kiro: thinking mode disabled via budget_tokens <= 0")
+				}
+			}
+			if thinkingEnabled {
+				log.Debugf("kiro: thinking mode enabled via Claude API parameter, budget_tokens: %d", budgetTokens)
+			}
+		}
+	}
+
+	return thinkingEnabled, budgetTokens
+}
+
+// IsThinkingEnabled is a public wrapper to check if thinking mode is enabled.
+// This is used by the executor to determine whether to parse <thinking> tags in responses.
+// When thinking is NOT enabled in the request, <thinking> tags in responses should be
+// treated as regular text content, not as thinking blocks.
+//
+// Supports multiple formats:
+// - Claude API format: thinking.type = "enabled"
+// - OpenAI format: reasoning_effort parameter
+// - AMP/Cursor format: <thinking_mode>interleaved</thinking_mode> in system prompt
+func IsThinkingEnabled(body []byte) bool {
+	// Check Claude API format first (thinking.type = "enabled")
+	enabled, _ := checkThinkingMode(body)
+	if enabled {
+		log.Debugf("kiro: IsThinkingEnabled returning true (Claude API format)")
+		return true
+	}
+
+	// Check OpenAI format: reasoning_effort parameter
+	// Valid values: "low", "medium", "high", "auto" (not "none")
+	reasoningEffort := gjson.GetBytes(body, "reasoning_effort")
+	if reasoningEffort.Exists() {
+		effort := reasoningEffort.String()
+		if effort != "" && effort != "none" {
+			log.Debugf("kiro: thinking mode enabled via OpenAI reasoning_effort: %s", effort)
+			return true
+		}
+	}
+
+	// Check AMP/Cursor format: <thinking_mode>interleaved</thinking_mode> in system prompt
+	// This is how AMP client passes thinking configuration
+	bodyStr := string(body)
+	if strings.Contains(bodyStr, "<thinking_mode>") && strings.Contains(bodyStr, "</thinking_mode>") {
+		// Extract thinking mode value
+		startTag := "<thinking_mode>"
+		endTag := "</thinking_mode>"
+		startIdx := strings.Index(bodyStr, startTag)
+		if startIdx >= 0 {
+			startIdx += len(startTag)
+			endIdx := strings.Index(bodyStr[startIdx:], endTag)
+			if endIdx >= 0 {
+				thinkingMode := bodyStr[startIdx : startIdx+endIdx]
+				if thinkingMode == "interleaved" || thinkingMode == "enabled" {
+					log.Debugf("kiro: thinking mode enabled via AMP/Cursor format: %s", thinkingMode)
+					return true
+				}
+			}
+		}
+	}
+
+	// Check OpenAI format: max_completion_tokens with reasoning (o1-style)
+	// Some clients use this to indicate reasoning mode
+	if gjson.GetBytes(body, "max_completion_tokens").Exists() {
+		// If max_completion_tokens is set, check if model name suggests reasoning
+		model := gjson.GetBytes(body, "model").String()
+		if strings.Contains(strings.ToLower(model), "thinking") ||
+			strings.Contains(strings.ToLower(model), "reason") {
+			log.Debugf("kiro: thinking mode enabled via model name hint: %s", model)
+			return true
+		}
+	}
+
+	log.Debugf("kiro: IsThinkingEnabled returning false (no thinking mode detected)")
+	return false
+}
+
+// shortenToolNameIfNeeded shortens tool names that exceed 64 characters.
+// MCP tools often have long names like "mcp__server-name__tool-name".
+// This preserves the "mcp__" prefix and last segment when possible.
+func shortenToolNameIfNeeded(name string) string {
+	const limit = 64
+	if len(name) <= limit {
+		return name
+	}
+	// For MCP tools, try to preserve prefix and last segment
+	if strings.HasPrefix(name, "mcp__") {
+		idx := strings.LastIndex(name, "__")
+		if idx > 0 {
+			cand := "mcp__" + name[idx+2:]
+			if len(cand) > limit {
+				return cand[:limit]
+			}
+			return cand
+		}
+	}
+	return name[:limit]
+}
+
+// convertClaudeToolsToKiro converts Claude tools to Kiro format
+func convertClaudeToolsToKiro(tools gjson.Result) []KiroToolWrapper {
+	var kiroTools []KiroToolWrapper
+	if !tools.IsArray() {
+		return kiroTools
+	}
+
+	for _, tool := range tools.Array() {
+		name := tool.Get("name").String()
+		description := tool.Get("description").String()
+		inputSchema := tool.Get("input_schema").Value()
+
+		// Shorten tool name if it exceeds 64 characters (common with MCP tools)
+		originalName := name
+		name = shortenToolNameIfNeeded(name)
+		if name != originalName {
+			log.Debugf("kiro: shortened tool name from '%s' to '%s'", originalName, name)
+		}
+
+		// CRITICAL FIX: Kiro API requires non-empty description
+		if strings.TrimSpace(description) == "" {
+			description = fmt.Sprintf("Tool: %s", name)
+			log.Debugf("kiro: tool '%s' has empty description, using default: %s", name, description)
+		}
+
+		// Truncate long descriptions
+		if len(description) > kirocommon.KiroMaxToolDescLen {
+			truncLen := kirocommon.KiroMaxToolDescLen - 30
+			for truncLen > 0 && !utf8.RuneStart(description[truncLen]) {
+				truncLen--
+			}
+			description = description[:truncLen] + "... (description truncated)"
+		}
+
+		kiroTools = append(kiroTools, KiroToolWrapper{
+			ToolSpecification: KiroToolSpecification{
+				Name:        name,
+				Description: description,
+				InputSchema: KiroInputSchema{JSON: inputSchema},
+			},
+		})
+	}
+
+	return kiroTools
+}
+
+// processMessages processes Claude messages and builds Kiro history
+func processMessages(messages gjson.Result, modelID, origin string) ([]KiroHistoryMessage, *KiroUserInputMessage, []KiroToolResult) {
+	var history []KiroHistoryMessage
+	var currentUserMsg *KiroUserInputMessage
+	var currentToolResults []KiroToolResult
+
+	// Merge adjacent messages with the same role
+	messagesArray := kirocommon.MergeAdjacentMessages(messages.Array())
+	for i, msg := range messagesArray {
+		role := msg.Get("role").String()
+		isLastMessage := i == len(messagesArray)-1
+
+		if role == "user" {
+			userMsg, toolResults := BuildUserMessageStruct(msg, modelID, origin)
+			if isLastMessage {
+				currentUserMsg = &userMsg
+				currentToolResults = toolResults
+			} else {
+				// CRITICAL: Kiro API requires content to be non-empty for history messages too
+				if strings.TrimSpace(userMsg.Content) == "" {
+					if len(toolResults) > 0 {
+						userMsg.Content = "Tool results provided."
+					} else {
+						userMsg.Content = "Continue"
+					}
+				}
+				// For history messages, embed tool results in context
+				if len(toolResults) > 0 {
+					userMsg.UserInputMessageContext = &KiroUserInputMessageContext{
+						ToolResults: toolResults,
+					}
+				}
+				history = append(history, KiroHistoryMessage{
+					UserInputMessage: &userMsg,
+				})
+			}
+		} else if role == "assistant" {
+			assistantMsg := BuildAssistantMessageStruct(msg)
+			if isLastMessage {
+				history = append(history, KiroHistoryMessage{
+					AssistantResponseMessage: &assistantMsg,
+				})
+				// Create a "Continue" user message as currentMessage
+				currentUserMsg = &KiroUserInputMessage{
+					Content: "Continue",
+					ModelID: modelID,
+					Origin:  origin,
+				}
+			} else {
+				history = append(history, KiroHistoryMessage{
+					AssistantResponseMessage: &assistantMsg,
+				})
+			}
+		}
+	}
+
+	return history, currentUserMsg, currentToolResults
+}
+
+// buildFinalContent builds the final content with system prompt
+func buildFinalContent(content, systemPrompt string, toolResults []KiroToolResult) string {
+	var contentBuilder strings.Builder
+
+	if systemPrompt != "" {
+		contentBuilder.WriteString("--- SYSTEM PROMPT ---\n")
+		contentBuilder.WriteString(systemPrompt)
+		contentBuilder.WriteString("\n--- END SYSTEM PROMPT ---\n\n")
+	}
+
+	contentBuilder.WriteString(content)
+	finalContent := contentBuilder.String()
+
+	// CRITICAL: Kiro API requires content to be non-empty
+	if strings.TrimSpace(finalContent) == "" {
+		if len(toolResults) > 0 {
+			finalContent = "Tool results provided."
+		} else {
+			finalContent = "Continue"
+		}
+		log.Debugf("kiro: content was empty, using default: %s", finalContent)
+	}
+
+	return finalContent
+}
+
+// deduplicateToolResults removes duplicate tool results
+func deduplicateToolResults(toolResults []KiroToolResult) []KiroToolResult {
+	if len(toolResults) == 0 {
+		return toolResults
+	}
+
+	seenIDs := make(map[string]bool)
+	unique := make([]KiroToolResult, 0, len(toolResults))
+	for _, tr := range toolResults {
+		if !seenIDs[tr.ToolUseID] {
+			seenIDs[tr.ToolUseID] = true
+			unique = append(unique, tr)
+		} else {
+			log.Debugf("kiro: skipping duplicate toolResult in currentMessage: %s", tr.ToolUseID)
+		}
+	}
+	return unique
+}
+
+// extractClaudeToolChoiceHint extracts tool_choice from Claude request and returns a system prompt hint.
+// Claude tool_choice values:
+// - {"type": "auto"}: Model decides (default, no hint needed)
+// - {"type": "any"}: Must use at least one tool
+// - {"type": "tool", "name": "..."}: Must use specific tool
+func extractClaudeToolChoiceHint(claudeBody []byte) string {
+	toolChoice := gjson.GetBytes(claudeBody, "tool_choice")
+	if !toolChoice.Exists() {
+		return ""
+	}
+
+	toolChoiceType := toolChoice.Get("type").String()
+	switch toolChoiceType {
+	case "any":
+		return "[INSTRUCTION: You MUST use at least one of the available tools to respond. Do not respond with text only - always make a tool call.]"
+	case "tool":
+		toolName := toolChoice.Get("name").String()
+		if toolName != "" {
+			return fmt.Sprintf("[INSTRUCTION: You MUST use the tool named '%s' to respond. Do not use any other tool or respond with text only.]", toolName)
+		}
+	case "auto":
+		// Default behavior, no hint needed
+		return ""
+	}
+
+	return ""
+}
+
+// BuildUserMessageStruct builds a user message and extracts tool results
+func BuildUserMessageStruct(msg gjson.Result, modelID, origin string) (KiroUserInputMessage, []KiroToolResult) {
+	content := msg.Get("content")
+	var contentBuilder strings.Builder
+	var toolResults []KiroToolResult
+	var images []KiroImage
+
+	// Track seen toolUseIds to deduplicate
+	seenToolUseIDs := make(map[string]bool)
+
+	if content.IsArray() {
+		for _, part := range content.Array() {
+			partType := part.Get("type").String()
+			switch partType {
+			case "text":
+				contentBuilder.WriteString(part.Get("text").String())
+			case "image":
+				mediaType := part.Get("source.media_type").String()
+				data := part.Get("source.data").String()
+
+				format := ""
+				if idx := strings.LastIndex(mediaType, "/"); idx != -1 {
+					format = mediaType[idx+1:]
+				}
+
+				if format != "" && data != "" {
+					images = append(images, KiroImage{
+						Format: format,
+						Source: KiroImageSource{
+							Bytes: data,
+						},
+					})
+				}
+			case "tool_result":
+				toolUseID := part.Get("tool_use_id").String()
+
+				// Skip duplicate toolUseIds
+				if seenToolUseIDs[toolUseID] {
+					log.Debugf("kiro: skipping duplicate tool_result with toolUseId: %s", toolUseID)
+					continue
+				}
+				seenToolUseIDs[toolUseID] = true
+
+				isError := part.Get("is_error").Bool()
+				resultContent := part.Get("content")
+
+				var textContents []KiroTextContent
+				if resultContent.IsArray() {
+					for _, item := range resultContent.Array() {
+						if item.Get("type").String() == "text" {
+							textContents = append(textContents, KiroTextContent{Text: item.Get("text").String()})
+						} else if item.Type == gjson.String {
+							textContents = append(textContents, KiroTextContent{Text: item.String()})
+						}
+					}
+				} else if resultContent.Type == gjson.String {
+					textContents = append(textContents, KiroTextContent{Text: resultContent.String()})
+				}
+
+				if len(textContents) == 0 {
+					textContents = append(textContents, KiroTextContent{Text: "Tool use was cancelled by the user"})
+				}
+
+				status := "success"
+				if isError {
+					status = "error"
+				}
+
+				toolResults = append(toolResults, KiroToolResult{
+					ToolUseID: toolUseID,
+					Content:   textContents,
+					Status:    status,
+				})
+			}
+		}
+	} else {
+		contentBuilder.WriteString(content.String())
+	}
+
+	userMsg := KiroUserInputMessage{
+		Content: contentBuilder.String(),
+		ModelID: modelID,
+		Origin:  origin,
+	}
+
+	if len(images) > 0 {
+		userMsg.Images = images
+	}
+
+	return userMsg, toolResults
+}
+
+// BuildAssistantMessageStruct builds an assistant message with tool uses
+func BuildAssistantMessageStruct(msg gjson.Result) KiroAssistantResponseMessage {
+	content := msg.Get("content")
+	var contentBuilder strings.Builder
+	var toolUses []KiroToolUse
+
+	if content.IsArray() {
+		for _, part := range content.Array() {
+			partType := part.Get("type").String()
+			switch partType {
+			case "text":
+				contentBuilder.WriteString(part.Get("text").String())
+			case "tool_use":
+				toolUseID := part.Get("id").String()
+				toolName := part.Get("name").String()
+				toolInput := part.Get("input")
+
+				var inputMap map[string]interface{}
+				if toolInput.IsObject() {
+					inputMap = make(map[string]interface{})
+					toolInput.ForEach(func(key, value gjson.Result) bool {
+						inputMap[key.String()] = value.Value()
+						return true
+					})
+				}
+
+				toolUses = append(toolUses, KiroToolUse{
+					ToolUseID: toolUseID,
+					Name:      toolName,
+					Input:     inputMap,
+				})
+			}
+		}
+	} else {
+		contentBuilder.WriteString(content.String())
+	}
+
+	return KiroAssistantResponseMessage{
+		Content:  contentBuilder.String(),
+		ToolUses: toolUses,
+	}
+}

internal/translator/kiro/claude/kiro_claude_response.go

@@ -0,0 +1,184 @@
+// Package claude provides response translation functionality for Kiro API to Claude format.
+// This package handles the conversion of Kiro API responses into Claude-compatible format,
+// including support for thinking blocks and tool use.
+package claude
+
+import (
+	"encoding/json"
+	"strings"
+
+	"github.com/google/uuid"
+	"github.com/router-for-me/CLIProxyAPI/v6/sdk/cliproxy/usage"
+	log "github.com/sirupsen/logrus"
+
+	kirocommon "github.com/router-for-me/CLIProxyAPI/v6/internal/translator/kiro/common"
+)
+
+// Local references to kirocommon constants for thinking block parsing
+var (
+	thinkingStartTag = kirocommon.ThinkingStartTag
+	thinkingEndTag   = kirocommon.ThinkingEndTag
+)
+
+// BuildClaudeResponse constructs a Claude-compatible response.
+// Supports tool_use blocks when tools are present in the response.
+// Supports thinking blocks - parses <thinking> tags and converts to Claude thinking content blocks.
+// stopReason is passed from upstream; fallback logic applied if empty.
+func BuildClaudeResponse(content string, toolUses []KiroToolUse, model string, usageInfo usage.Detail, stopReason string) []byte {
+	var contentBlocks []map[string]interface{}
+
+	// Extract thinking blocks and text from content
+	if content != "" {
+		blocks := ExtractThinkingFromContent(content)
+		contentBlocks = append(contentBlocks, blocks...)
+
+		// Log if thinking blocks were extracted
+		for _, block := range blocks {
+			if block["type"] == "thinking" {
+				thinkingContent := block["thinking"].(string)
+				log.Infof("kiro: buildClaudeResponse extracted thinking block (len: %d)", len(thinkingContent))
+			}
+		}
+	}
+
+	// Add tool_use blocks
+	for _, toolUse := range toolUses {
+		contentBlocks = append(contentBlocks, map[string]interface{}{
+			"type":  "tool_use",
+			"id":    toolUse.ToolUseID,
+			"name":  toolUse.Name,
+			"input": toolUse.Input,
+		})
+	}
+
+	// Ensure at least one content block (Claude API requires non-empty content)
+	if len(contentBlocks) == 0 {
+		contentBlocks = append(contentBlocks, map[string]interface{}{
+			"type": "text",
+			"text": "",
+		})
+	}
+
+	// Use upstream stopReason; apply fallback logic if not provided
+	if stopReason == "" {
+		stopReason = "end_turn"
+		if len(toolUses) > 0 {
+			stopReason = "tool_use"
+		}
+		log.Debugf("kiro: buildClaudeResponse using fallback stop_reason: %s", stopReason)
+	}
+
+	// Log warning if response was truncated due to max_tokens
+	if stopReason == "max_tokens" {
+		log.Warnf("kiro: response truncated due to max_tokens limit (buildClaudeResponse)")
+	}
+
+	response := map[string]interface{}{
+		"id":          "msg_" + uuid.New().String()[:24],
+		"type":        "message",
+		"role":        "assistant",
+		"model":       model,
+		"content":     contentBlocks,
+		"stop_reason": stopReason,
+		"usage": map[string]interface{}{
+			"input_tokens":  usageInfo.InputTokens,
+			"output_tokens": usageInfo.OutputTokens,
+		},
+	}
+	result, _ := json.Marshal(response)
+	return result
+}
+
+// ExtractThinkingFromContent parses content to extract thinking blocks and text.
+// Returns a list of content blocks in the order they appear in the content.
+// Handles interleaved thinking and text blocks correctly.
+func ExtractThinkingFromContent(content string) []map[string]interface{} {
+	var blocks []map[string]interface{}
+
+	if content == "" {
+		return blocks
+	}
+
+	// Check if content contains thinking tags at all
+	if !strings.Contains(content, thinkingStartTag) {
+		// No thinking tags, return as plain text
+		return []map[string]interface{}{
+			{
+				"type": "text",
+				"text": content,
+			},
+		}
+	}
+
+	log.Debugf("kiro: extractThinkingFromContent - found thinking tags in content (len: %d)", len(content))
+
+	remaining := content
+
+	for len(remaining) > 0 {
+		// Look for <thinking> tag
+		startIdx := strings.Index(remaining, thinkingStartTag)
+
+		if startIdx == -1 {
+			// No more thinking tags, add remaining as text
+			if strings.TrimSpace(remaining) != "" {
+				blocks = append(blocks, map[string]interface{}{
+					"type": "text",
+					"text": remaining,
+				})
+			}
+			break
+		}
+
+		// Add text before thinking tag (if any meaningful content)
+		if startIdx > 0 {
+			textBefore := remaining[:startIdx]
+			if strings.TrimSpace(textBefore) != "" {
+				blocks = append(blocks, map[string]interface{}{
+					"type": "text",
+					"text": textBefore,
+				})
+			}
+		}
+
+		// Move past the opening tag
+		remaining = remaining[startIdx+len(thinkingStartTag):]
+
+		// Find closing tag
+		endIdx := strings.Index(remaining, thinkingEndTag)
+
+		if endIdx == -1 {
+			// No closing tag found, treat rest as thinking content (incomplete response)
+			if strings.TrimSpace(remaining) != "" {
+				blocks = append(blocks, map[string]interface{}{
+					"type":     "thinking",
+					"thinking": remaining,
+				})
+				log.Warnf("kiro: extractThinkingFromContent - missing closing </thinking> tag")
+			}
+			break
+		}
+
+		// Extract thinking content between tags
+		thinkContent := remaining[:endIdx]
+		if strings.TrimSpace(thinkContent) != "" {
+			blocks = append(blocks, map[string]interface{}{
+				"type":     "thinking",
+				"thinking": thinkContent,
+			})
+			log.Debugf("kiro: extractThinkingFromContent - extracted thinking block (len: %d)", len(thinkContent))
+		}
+
+		// Move past the closing tag
+		remaining = remaining[endIdx+len(thinkingEndTag):]
+	}
+
+	// If no blocks were created (all whitespace), return empty text block
+	if len(blocks) == 0 {
+		blocks = append(blocks, map[string]interface{}{
+			"type": "text",
+			"text": "",
+		})
+	}
+
+	return blocks
+}

internal/translator/kiro/claude/kiro_claude_stream.go

@@ -0,0 +1,176 @@
+// Package claude provides streaming SSE event building for Claude format.
+// This package handles the construction of Claude-compatible Server-Sent Events (SSE)
+// for streaming responses from Kiro API.
+package claude
+
+import (
+	"encoding/json"
+
+	"github.com/google/uuid"
+	"github.com/router-for-me/CLIProxyAPI/v6/sdk/cliproxy/usage"
+)
+
+// BuildClaudeMessageStartEvent creates the message_start SSE event
+func BuildClaudeMessageStartEvent(model string, inputTokens int64) []byte {
+	event := map[string]interface{}{
+		"type": "message_start",
+		"message": map[string]interface{}{
+			"id":            "msg_" + uuid.New().String()[:24],
+			"type":          "message",
+			"role":          "assistant",
+			"content":       []interface{}{},
+			"model":         model,
+			"stop_reason":   nil,
+			"stop_sequence": nil,
+			"usage":         map[string]interface{}{"input_tokens": inputTokens, "output_tokens": 0},
+		},
+	}
+	result, _ := json.Marshal(event)
+	return []byte("event: message_start\ndata: " + string(result))
+}
+
+// BuildClaudeContentBlockStartEvent creates a content_block_start SSE event
+func BuildClaudeContentBlockStartEvent(index int, blockType, toolUseID, toolName string) []byte {
+	var contentBlock map[string]interface{}
+	switch blockType {
+	case "tool_use":
+		contentBlock = map[string]interface{}{
+			"type":  "tool_use",
+			"id":    toolUseID,
+			"name":  toolName,
+			"input": map[string]interface{}{},
+		}
+	case "thinking":
+		contentBlock = map[string]interface{}{
+			"type":     "thinking",
+			"thinking": "",
+		}
+	default:
+		contentBlock = map[string]interface{}{
+			"type": "text",
+			"text": "",
+		}
+	}
+
+	event := map[string]interface{}{
+		"type":          "content_block_start",
+		"index":         index,
+		"content_block": contentBlock,
+	}
+	result, _ := json.Marshal(event)
+	return []byte("event: content_block_start\ndata: " + string(result))
+}
+
+// BuildClaudeStreamEvent creates a text_delta content_block_delta SSE event
+func BuildClaudeStreamEvent(contentDelta string, index int) []byte {
+	event := map[string]interface{}{
+		"type":  "content_block_delta",
+		"index": index,
+		"delta": map[string]interface{}{
+			"type": "text_delta",
+			"text": contentDelta,
+		},
+	}
+	result, _ := json.Marshal(event)
+	return []byte("event: content_block_delta\ndata: " + string(result))
+}
+
+// BuildClaudeInputJsonDeltaEvent creates an input_json_delta event for tool use streaming
+func BuildClaudeInputJsonDeltaEvent(partialJSON string, index int) []byte {
+	event := map[string]interface{}{
+		"type":  "content_block_delta",
+		"index": index,
+		"delta": map[string]interface{}{
+			"type":         "input_json_delta",
+			"partial_json": partialJSON,
+		},
+	}
+	result, _ := json.Marshal(event)
+	return []byte("event: content_block_delta\ndata: " + string(result))
+}
+
+// BuildClaudeContentBlockStopEvent creates a content_block_stop SSE event
+func BuildClaudeContentBlockStopEvent(index int) []byte {
+	event := map[string]interface{}{
+		"type":  "content_block_stop",
+		"index": index,
+	}
+	result, _ := json.Marshal(event)
+	return []byte("event: content_block_stop\ndata: " + string(result))
+}
+
+// BuildClaudeMessageDeltaEvent creates the message_delta event with stop_reason and usage
+func BuildClaudeMessageDeltaEvent(stopReason string, usageInfo usage.Detail) []byte {
+	deltaEvent := map[string]interface{}{
+		"type": "message_delta",
+		"delta": map[string]interface{}{
+			"stop_reason":   stopReason,
+			"stop_sequence": nil,
+		},
+		"usage": map[string]interface{}{
+			"input_tokens":  usageInfo.InputTokens,
+			"output_tokens": usageInfo.OutputTokens,
+		},
+	}
+	deltaResult, _ := json.Marshal(deltaEvent)
+	return []byte("event: message_delta\ndata: " + string(deltaResult))
+}
+
+// BuildClaudeMessageStopOnlyEvent creates only the message_stop event
+func BuildClaudeMessageStopOnlyEvent() []byte {
+	stopEvent := map[string]interface{}{
+		"type": "message_stop",
+	}
+	stopResult, _ := json.Marshal(stopEvent)
+	return []byte("event: message_stop\ndata: " + string(stopResult))
+}
+
+// BuildClaudePingEventWithUsage creates a ping event with embedded usage information.
+// This is used for real-time usage estimation during streaming.
+func BuildClaudePingEventWithUsage(inputTokens, outputTokens int64) []byte {
+	event := map[string]interface{}{
+		"type": "ping",
+		"usage": map[string]interface{}{
+			"input_tokens":  inputTokens,
+			"output_tokens": outputTokens,
+			"total_tokens":  inputTokens + outputTokens,
+			"estimated":     true,
+		},
+	}
+	result, _ := json.Marshal(event)
+	return []byte("event: ping\ndata: " + string(result))
+}
+
+// BuildClaudeThinkingDeltaEvent creates a thinking_delta event for Claude API compatibility.
+// This is used when streaming thinking content wrapped in <thinking> tags.
+func BuildClaudeThinkingDeltaEvent(thinkingDelta string, index int) []byte {
+	event := map[string]interface{}{
+		"type":  "content_block_delta",
+		"index": index,
+		"delta": map[string]interface{}{
+			"type":     "thinking_delta",
+			"thinking": thinkingDelta,
+		},
+	}
+	result, _ := json.Marshal(event)
+	return []byte("event: content_block_delta\ndata: " + string(result))
+}
+
+// PendingTagSuffix detects if the buffer ends with a partial prefix of the given tag.
+// Returns the length of the partial match (0 if no match).
+// Based on amq2api implementation for handling cross-chunk tag boundaries.
+func PendingTagSuffix(buffer, tag string) int {
+	if buffer == "" || tag == "" {
+		return 0
+	}
+	maxLen := len(buffer)
+	if maxLen > len(tag)-1 {
+		maxLen = len(tag) - 1
+	}
+	for length := maxLen; length > 0; length-- {
+		if len(buffer) >= length && buffer[len(buffer)-length:] == tag[:length] {
+			return length
+		}
+	}
+	return 0
+}

internal/translator/kiro/claude/kiro_claude_tools.go

@@ -0,0 +1,522 @@
+// Package claude provides tool calling support for Kiro to Claude translation.
+// This package handles parsing embedded tool calls, JSON repair, and deduplication.
+package claude
+
+import (
+	"encoding/json"
+	"regexp"
+	"strings"
+
+	"github.com/google/uuid"
+	kirocommon "github.com/router-for-me/CLIProxyAPI/v6/internal/translator/kiro/common"
+	log "github.com/sirupsen/logrus"
+)
+
+// ToolUseState tracks the state of an in-progress tool use during streaming.
+type ToolUseState struct {
+	ToolUseID   string
+	Name        string
+	InputBuffer strings.Builder
+	IsComplete  bool
+}
+
+// Pre-compiled regex patterns for performance
+var (
+	// embeddedToolCallPattern matches [Called tool_name with args: {...}] format
+	embeddedToolCallPattern = regexp.MustCompile(`\[Called\s+([A-Za-z0-9_.-]+)\s+with\s+args:\s*`)
+	// trailingCommaPattern matches trailing commas before closing braces/brackets
+	trailingCommaPattern = regexp.MustCompile(`,\s*([}\]])`)
+)
+
+// ParseEmbeddedToolCalls extracts [Called tool_name with args: {...}] format from text.
+// Kiro sometimes embeds tool calls in text content instead of using toolUseEvent.
+// Returns the cleaned text (with tool calls removed) and extracted tool uses.
+func ParseEmbeddedToolCalls(text string, processedIDs map[string]bool) (string, []KiroToolUse) {
+	if !strings.Contains(text, "[Called") {
+		return text, nil
+	}
+
+	var toolUses []KiroToolUse
+	cleanText := text
+
+	// Find all [Called markers
+	matches := embeddedToolCallPattern.FindAllStringSubmatchIndex(text, -1)
+	if len(matches) == 0 {
+		return text, nil
+	}
+
+	// Process matches in reverse order to maintain correct indices
+	for i := len(matches) - 1; i >= 0; i-- {
+		matchStart := matches[i][0]
+		toolNameStart := matches[i][2]
+		toolNameEnd := matches[i][3]
+
+		if toolNameStart < 0 || toolNameEnd < 0 {
+			continue
+		}
+
+		toolName := text[toolNameStart:toolNameEnd]
+
+		// Find the JSON object start (after "with args:")
+		jsonStart := matches[i][1]
+		if jsonStart >= len(text) {
+			continue
+		}
+
+		// Skip whitespace to find the opening brace
+		for jsonStart < len(text) && (text[jsonStart] == ' ' || text[jsonStart] == '\t') {
+			jsonStart++
+		}
+
+		if jsonStart >= len(text) || text[jsonStart] != '{' {
+			continue
+		}
+
+		// Find matching closing bracket
+		jsonEnd := findMatchingBracket(text, jsonStart)
+		if jsonEnd < 0 {
+			continue
+		}
+
+		// Extract JSON and find the closing bracket of [Called ...]
+		jsonStr := text[jsonStart : jsonEnd+1]
+
+		// Find the closing ] after the JSON
+		closingBracket := jsonEnd + 1
+		for closingBracket < len(text) && text[closingBracket] != ']' {
+			closingBracket++
+		}
+		if closingBracket >= len(text) {
+			continue
+		}
+
+		// End index of the full tool call (closing ']' inclusive)
+		matchEnd := closingBracket + 1
+
+		// Repair and parse JSON
+		repairedJSON := RepairJSON(jsonStr)
+		var inputMap map[string]interface{}
+		if err := json.Unmarshal([]byte(repairedJSON), &inputMap); err != nil {
+			log.Debugf("kiro: failed to parse embedded tool call JSON: %v, raw: %s", err, jsonStr)
+			continue
+		}
+
+		// Generate unique tool ID
+		toolUseID := "toolu_" + uuid.New().String()[:12]
+
+		// Check for duplicates using name+input as key
+		dedupeKey := toolName + ":" + repairedJSON
+		if processedIDs != nil {
+			if processedIDs[dedupeKey] {
+				log.Debugf("kiro: skipping duplicate embedded tool call: %s", toolName)
+				// Still remove from text even if duplicate
+				if matchStart >= 0 && matchEnd <= len(cleanText) && matchStart <= matchEnd {
+					cleanText = cleanText[:matchStart] + cleanText[matchEnd:]
+				}
+				continue
+			}
+			processedIDs[dedupeKey] = true
+		}
+
+		toolUses = append(toolUses, KiroToolUse{
+			ToolUseID: toolUseID,
+			Name:      toolName,
+			Input:     inputMap,
+		})
+
+		log.Infof("kiro: extracted embedded tool call: %s (ID: %s)", toolName, toolUseID)
+
+		// Remove from clean text (index-based removal to avoid deleting the wrong occurrence)
+		if matchStart >= 0 && matchEnd <= len(cleanText) && matchStart <= matchEnd {
+			cleanText = cleanText[:matchStart] + cleanText[matchEnd:]
+		}
+	}
+
+	return cleanText, toolUses
+}
+
+// findMatchingBracket finds the index of the closing brace/bracket that matches
+// the opening one at startPos. Handles nested objects and strings correctly.
+func findMatchingBracket(text string, startPos int) int {
+	if startPos >= len(text) {
+		return -1
+	}
+
+	openChar := text[startPos]
+	var closeChar byte
+	switch openChar {
+	case '{':
+		closeChar = '}'
+	case '[':
+		closeChar = ']'
+	default:
+		return -1
+	}
+
+	depth := 1
+	inString := false
+	escapeNext := false
+
+	for i := startPos + 1; i < len(text); i++ {
+		char := text[i]
+
+		if escapeNext {
+			escapeNext = false
+			continue
+		}
+
+		if char == '\\' && inString {
+			escapeNext = true
+			continue
+		}
+
+		if char == '"' {
+			inString = !inString
+			continue
+		}
+
+		if !inString {
+			if char == openChar {
+				depth++
+			} else if char == closeChar {
+				depth--
+				if depth == 0 {
+					return i
+				}
+			}
+		}
+	}
+
+	return -1
+}
+
+// RepairJSON attempts to fix common JSON issues that may occur in tool call arguments.
+// Conservative repair strategy:
+// 1. First try to parse JSON directly - if valid, return as-is
+// 2. Only attempt repair if parsing fails
+// 3. After repair, validate the result - if still invalid, return original
+func RepairJSON(jsonString string) string {
+	// Handle empty or invalid input
+	if jsonString == "" {
+		return "{}"
+	}
+
+	str := strings.TrimSpace(jsonString)
+	if str == "" {
+		return "{}"
+	}
+
+	// CONSERVATIVE STRATEGY: First try to parse directly
+	var testParse interface{}
+	if err := json.Unmarshal([]byte(str), &testParse); err == nil {
+		log.Debugf("kiro: repairJSON - JSON is already valid, returning unchanged")
+		return str
+	}
+
+	log.Debugf("kiro: repairJSON - JSON parse failed, attempting repair")
+	originalStr := str
+
+	// First, escape unescaped newlines/tabs within JSON string values
+	str = escapeNewlinesInStrings(str)
+	// Remove trailing commas before closing braces/brackets
+	str = trailingCommaPattern.ReplaceAllString(str, "$1")
+
+	// Calculate bracket balance
+	braceCount := 0
+	bracketCount := 0
+	inString := false
+	escape := false
+	lastValidIndex := -1
+
+	for i := 0; i < len(str); i++ {
+		char := str[i]
+
+		if escape {
+			escape = false
+			continue
+		}
+
+		if char == '\\' {
+			escape = true
+			continue
+		}
+
+		if char == '"' {
+			inString = !inString
+			continue
+		}
+
+		if inString {
+			continue
+		}
+
+		switch char {
+		case '{':
+			braceCount++
+		case '}':
+			braceCount--
+		case '[':
+			bracketCount++
+		case ']':
+			bracketCount--
+		}
+
+		if braceCount >= 0 && bracketCount >= 0 {
+			lastValidIndex = i
+		}
+	}
+
+	// If brackets are unbalanced, try to repair
+	if braceCount > 0 || bracketCount > 0 {
+		if lastValidIndex > 0 && lastValidIndex < len(str)-1 {
+			truncated := str[:lastValidIndex+1]
+			// Recount brackets after truncation
+			braceCount = 0
+			bracketCount = 0
+			inString = false
+			escape = false
+			for i := 0; i < len(truncated); i++ {
+				char := truncated[i]
+				if escape {
+					escape = false
+					continue
+				}
+				if char == '\\' {
+					escape = true
+					continue
+				}
+				if char == '"' {
+					inString = !inString
+					continue
+				}
+				if inString {
+					continue
+				}
+				switch char {
+				case '{':
+					braceCount++
+				case '}':
+					braceCount--
+				case '[':
+					bracketCount++
+				case ']':
+					bracketCount--
+				}
+			}
+			str = truncated
+		}
+
+		// Add missing closing brackets
+		for braceCount > 0 {
+			str += "}"
+			braceCount--
+		}
+		for bracketCount > 0 {
+			str += "]"
+			bracketCount--
+		}
+	}
+
+	// Validate repaired JSON
+	if err := json.Unmarshal([]byte(str), &testParse); err != nil {
+		log.Warnf("kiro: repairJSON - repair failed to produce valid JSON, returning original")
+		return originalStr
+	}
+
+	log.Debugf("kiro: repairJSON - successfully repaired JSON")
+	return str
+}
+
+// escapeNewlinesInStrings escapes literal newlines, tabs, and other control characters
+// that appear inside JSON string values.
+func escapeNewlinesInStrings(raw string) string {
+	var result strings.Builder
+	result.Grow(len(raw) + 100)
+
+	inString := false
+	escaped := false
+
+	for i := 0; i < len(raw); i++ {
+		c := raw[i]
+
+		if escaped {
+			result.WriteByte(c)
+			escaped = false
+			continue
+		}
+
+		if c == '\\' && inString {
+			result.WriteByte(c)
+			escaped = true
+			continue
+		}
+
+		if c == '"' {
+			inString = !inString
+			result.WriteByte(c)
+			continue
+		}
+
+		if inString {
+			switch c {
+			case '\n':
+				result.WriteString("\\n")
+			case '\r':
+				result.WriteString("\\r")
+			case '\t':
+				result.WriteString("\\t")
+			default:
+				result.WriteByte(c)
+			}
+		} else {
+			result.WriteByte(c)
+		}
+	}
+
+	return result.String()
+}
+
+// ProcessToolUseEvent handles a toolUseEvent from the Kiro stream.
+// It accumulates input fragments and emits tool_use blocks when complete.
+// Returns events to emit and updated state.
+func ProcessToolUseEvent(event map[string]interface{}, currentToolUse *ToolUseState, processedIDs map[string]bool) ([]KiroToolUse, *ToolUseState) {
+	var toolUses []KiroToolUse
+
+	// Extract from nested toolUseEvent or direct format
+	tu := event
+	if nested, ok := event["toolUseEvent"].(map[string]interface{}); ok {
+		tu = nested
+	}
+
+	toolUseID := kirocommon.GetString(tu, "toolUseId")
+	toolName := kirocommon.GetString(tu, "name")
+	isStop := false
+	if stop, ok := tu["stop"].(bool); ok {
+		isStop = stop
+	}
+
+	// Get input - can be string (fragment) or object (complete)
+	var inputFragment string
+	var inputMap map[string]interface{}
+
+	if inputRaw, ok := tu["input"]; ok {
+		switch v := inputRaw.(type) {
+		case string:
+			inputFragment = v
+		case map[string]interface{}:
+			inputMap = v
+		}
+	}
+
+	// New tool use starting
+	if toolUseID != "" && toolName != "" {
+		if currentToolUse != nil && currentToolUse.ToolUseID != toolUseID {
+			log.Warnf("kiro: interleaved tool use detected - new ID %s arrived while %s in progress, completing previous",
+				toolUseID, currentToolUse.ToolUseID)
+			if !processedIDs[currentToolUse.ToolUseID] {
+				incomplete := KiroToolUse{
+					ToolUseID: currentToolUse.ToolUseID,
+					Name:      currentToolUse.Name,
+				}
+				if currentToolUse.InputBuffer.Len() > 0 {
+					raw := currentToolUse.InputBuffer.String()
+					repaired := RepairJSON(raw)
+
+					var input map[string]interface{}
+					if err := json.Unmarshal([]byte(repaired), &input); err != nil {
+						log.Warnf("kiro: failed to parse interleaved tool input: %v, raw: %s", err, raw)
+						input = make(map[string]interface{})
+					}
+					incomplete.Input = input
+				}
+				toolUses = append(toolUses, incomplete)
+				processedIDs[currentToolUse.ToolUseID] = true
+			}
+			currentToolUse = nil
+		}
+
+		if currentToolUse == nil {
+			if processedIDs != nil && processedIDs[toolUseID] {
+				log.Debugf("kiro: skipping duplicate toolUseEvent: %s", toolUseID)
+				return nil, nil
+			}
+
+			currentToolUse = &ToolUseState{
+				ToolUseID: toolUseID,
+				Name:      toolName,
+			}
+			log.Infof("kiro: starting new tool use: %s (ID: %s)", toolName, toolUseID)
+		}
+	}
+
+	// Accumulate input fragments
+	if currentToolUse != nil && inputFragment != "" {
+		currentToolUse.InputBuffer.WriteString(inputFragment)
+		log.Debugf("kiro: accumulated input fragment, total length: %d", currentToolUse.InputBuffer.Len())
+	}
+
+	// If complete input object provided directly
+	if currentToolUse != nil && inputMap != nil {
+		inputBytes, _ := json.Marshal(inputMap)
+		currentToolUse.InputBuffer.Reset()
+		currentToolUse.InputBuffer.Write(inputBytes)
+	}
+
+	// Tool use complete
+	if isStop && currentToolUse != nil {
+		fullInput := currentToolUse.InputBuffer.String()
+
+		// Repair and parse the accumulated JSON
+		repairedJSON := RepairJSON(fullInput)
+		var finalInput map[string]interface{}
+		if err := json.Unmarshal([]byte(repairedJSON), &finalInput); err != nil {
+			log.Warnf("kiro: failed to parse accumulated tool input: %v, raw: %s", err, fullInput)
+			finalInput = make(map[string]interface{})
+		}
+
+		toolUse := KiroToolUse{
+			ToolUseID: currentToolUse.ToolUseID,
+			Name:      currentToolUse.Name,
+			Input:     finalInput,
+		}
+		toolUses = append(toolUses, toolUse)
+
+		if processedIDs != nil {
+			processedIDs[currentToolUse.ToolUseID] = true
+		}
+
+		log.Infof("kiro: completed tool use: %s (ID: %s)", currentToolUse.Name, currentToolUse.ToolUseID)
+		return toolUses, nil
+	}
+
+	return toolUses, currentToolUse
+}
+
+// DeduplicateToolUses removes duplicate tool uses based on toolUseId and content.
+func DeduplicateToolUses(toolUses []KiroToolUse) []KiroToolUse {
+	seenIDs := make(map[string]bool)
+	seenContent := make(map[string]bool)
+	var unique []KiroToolUse
+
+	for _, tu := range toolUses {
+		if seenIDs[tu.ToolUseID] {
+			log.Debugf("kiro: removing ID-duplicate tool use: %s (name: %s)", tu.ToolUseID, tu.Name)
+			continue
+		}
+
+		inputJSON, _ := json.Marshal(tu.Input)
+		contentKey := tu.Name + ":" + string(inputJSON)
+
+		if seenContent[contentKey] {
+			log.Debugf("kiro: removing content-duplicate tool use: %s (id: %s)", tu.Name, tu.ToolUseID)
+			continue
+		}
+
+		seenIDs[tu.ToolUseID] = true
+		seenContent[contentKey] = true
+		unique = append(unique, tu)
+	}
+
+	return unique
+}
+

internal/translator/kiro/common/constants.go

@@ -0,0 +1,75 @@
+// Package common provides shared constants and utilities for Kiro translator.
+package common
+
+const (
+	// KiroMaxToolDescLen is the maximum description length for Kiro API tools.
+	// Kiro API limit is 10240 bytes, leave room for "..."
+	KiroMaxToolDescLen = 10237
+
+	// ThinkingStartTag is the start tag for thinking blocks in responses.
+	ThinkingStartTag = "<thinking>"
+
+	// ThinkingEndTag is the end tag for thinking blocks in responses.
+	ThinkingEndTag = "</thinking>"
+
+	// CodeFenceMarker is the markdown code fence marker.
+	CodeFenceMarker = "```"
+
+	// AltCodeFenceMarker is the alternative markdown code fence marker.
+	AltCodeFenceMarker = "~~~"
+
+	// InlineCodeMarker is the markdown inline code marker (backtick).
+	InlineCodeMarker = "`"
+
+	// KiroAgenticSystemPrompt is injected only for -agentic models to prevent timeouts on large writes.
+	// AWS Kiro API has a 2-3 minute timeout for large file write operations.
+	KiroAgenticSystemPrompt = `
+# CRITICAL: CHUNKED WRITE PROTOCOL (MANDATORY)
+
+You MUST follow these rules for ALL file operations. Violation causes server timeouts and task failure.
+
+## ABSOLUTE LIMITS
+- **MAXIMUM 350 LINES** per single write/edit operation - NO EXCEPTIONS
+- **RECOMMENDED 300 LINES** or less for optimal performance
+- **NEVER** write entire files in one operation if >300 lines
+
+## MANDATORY CHUNKED WRITE STRATEGY
+
+### For NEW FILES (>300 lines total):
+1. FIRST: Write initial chunk (first 250-300 lines) using write_to_file/fsWrite
+2. THEN: Append remaining content in 250-300 line chunks using file append operations
+3. REPEAT: Continue appending until complete
+
+### For EDITING EXISTING FILES:
+1. Use surgical edits (apply_diff/targeted edits) - change ONLY what's needed
+2. NEVER rewrite entire files - use incremental modifications
+3. Split large refactors into multiple small, focused edits
+
+### For LARGE CODE GENERATION:
+1. Generate in logical sections (imports, types, functions separately)
+2. Write each section as a separate operation
+3. Use append operations for subsequent sections
+
+## EXAMPLES OF CORRECT BEHAVIOR
+
+✅ CORRECT: Writing a 600-line file
+- Operation 1: Write lines 1-300 (initial file creation)
+- Operation 2: Append lines 301-600
+
+✅ CORRECT: Editing multiple functions
+- Operation 1: Edit function A
+- Operation 2: Edit function B
+- Operation 3: Edit function C
+
+❌ WRONG: Writing 500 lines in single operation → TIMEOUT
+❌ WRONG: Rewriting entire file to change 5 lines → TIMEOUT
+❌ WRONG: Generating massive code blocks without chunking → TIMEOUT
+
+## WHY THIS MATTERS
+- Server has 2-3 minute timeout for operations
+- Large writes exceed timeout and FAIL completely
+- Chunked writes are FASTER and more RELIABLE
+- Failed writes waste time and require retry
+
+REMEMBER: When in doubt, write LESS per operation. Multiple small operations > one large operation.`
+)

internal/translator/kiro/common/message_merge.go

@@ -0,0 +1,125 @@
+// Package common provides shared utilities for Kiro translators.
+package common
+
+import (
+	"encoding/json"
+
+	"github.com/tidwall/gjson"
+)
+
+// MergeAdjacentMessages merges adjacent messages with the same role.
+// This reduces API call complexity and improves compatibility.
+// Based on AIClient-2-API implementation.
+func MergeAdjacentMessages(messages []gjson.Result) []gjson.Result {
+	if len(messages) <= 1 {
+		return messages
+	}
+
+	var merged []gjson.Result
+	for _, msg := range messages {
+		if len(merged) == 0 {
+			merged = append(merged, msg)
+			continue
+		}
+
+		lastMsg := merged[len(merged)-1]
+		currentRole := msg.Get("role").String()
+		lastRole := lastMsg.Get("role").String()
+
+		if currentRole == lastRole {
+			// Merge content from current message into last message
+			mergedContent := mergeMessageContent(lastMsg, msg)
+			// Create a new merged message JSON
+			mergedMsg := createMergedMessage(lastRole, mergedContent)
+			merged[len(merged)-1] = gjson.Parse(mergedMsg)
+		} else {
+			merged = append(merged, msg)
+		}
+	}
+
+	return merged
+}
+
+// mergeMessageContent merges the content of two messages with the same role.
+// Handles both string content and array content (with text, tool_use, tool_result blocks).
+func mergeMessageContent(msg1, msg2 gjson.Result) string {
+	content1 := msg1.Get("content")
+	content2 := msg2.Get("content")
+
+	// Extract content blocks from both messages
+	var blocks1, blocks2 []map[string]interface{}
+
+	if content1.IsArray() {
+		for _, block := range content1.Array() {
+			blocks1 = append(blocks1, blockToMap(block))
+		}
+	} else if content1.Type == gjson.String {
+		blocks1 = append(blocks1, map[string]interface{}{
+			"type": "text",
+			"text": content1.String(),
+		})
+	}
+
+	if content2.IsArray() {
+		for _, block := range content2.Array() {
+			blocks2 = append(blocks2, blockToMap(block))
+		}
+	} else if content2.Type == gjson.String {
+		blocks2 = append(blocks2, map[string]interface{}{
+			"type": "text",
+			"text": content2.String(),
+		})
+	}
+
+	// Merge text blocks if both end/start with text
+	if len(blocks1) > 0 && len(blocks2) > 0 {
+		if blocks1[len(blocks1)-1]["type"] == "text" && blocks2[0]["type"] == "text" {
+			// Merge the last text block of msg1 with the first text block of msg2
+			text1 := blocks1[len(blocks1)-1]["text"].(string)
+			text2 := blocks2[0]["text"].(string)
+			blocks1[len(blocks1)-1]["text"] = text1 + "\n" + text2
+			blocks2 = blocks2[1:] // Remove the merged block from blocks2
+		}
+	}
+
+	// Combine all blocks
+	allBlocks := append(blocks1, blocks2...)
+
+	// Convert to JSON
+	result, _ := json.Marshal(allBlocks)
+	return string(result)
+}
+
+// blockToMap converts a gjson.Result block to a map[string]interface{}
+func blockToMap(block gjson.Result) map[string]interface{} {
+	result := make(map[string]interface{})
+	block.ForEach(func(key, value gjson.Result) bool {
+		if value.IsObject() {
+			result[key.String()] = blockToMap(value)
+		} else if value.IsArray() {
+			var arr []interface{}
+			for _, item := range value.Array() {
+				if item.IsObject() {
+					arr = append(arr, blockToMap(item))
+				} else {
+					arr = append(arr, item.Value())
+				}
+			}
+			result[key.String()] = arr
+		} else {
+			result[key.String()] = value.Value()
+		}
+		return true
+	})
+	return result
+}
+
+// createMergedMessage creates a JSON string for a merged message
+func createMergedMessage(role string, content string) string {
+	msg := map[string]interface{}{
+		"role":    role,
+		"content": json.RawMessage(content),
+	}
+	result, _ := json.Marshal(msg)
+	return string(result)
+}

internal/translator/kiro/common/utils.go

@@ -0,0 +1,16 @@
+// Package common provides shared constants and utilities for Kiro translator.
+package common
+
+// GetString safely extracts a string from a map.
+// Returns empty string if the key doesn't exist or the value is not a string.
+func GetString(m map[string]interface{}, key string) string {
+	if v, ok := m[key].(string); ok {
+		return v
+	}
+	return ""
+}
+
+// GetStringValue is an alias for GetString for backward compatibility.
+func GetStringValue(m map[string]interface{}, key string) string {
+	return GetString(m, key)
+}

internal/translator/kiro/openai/chat-completions/kiro_openai_request.go

@@ -1,348 +0,0 @@
-// Package chat_completions provides request translation from OpenAI to Kiro format.
-package chat_completions
-
-import (
-	"bytes"
-	"encoding/json"
-	"strings"
-
-	"github.com/tidwall/gjson"
-	"github.com/tidwall/sjson"
-)
-
-// reasoningEffortToBudget maps OpenAI reasoning_effort values to Claude thinking budget_tokens.
-// OpenAI uses "low", "medium", "high" while Claude uses numeric budget_tokens.
-var reasoningEffortToBudget = map[string]int{
-	"low":    4000,
-	"medium": 16000,
-	"high":   32000,
-}
-
-// ConvertOpenAIRequestToKiro transforms an OpenAI Chat Completions API request into Kiro (Claude) format.
-// Kiro uses Claude-compatible format internally, so we primarily pass through to Claude format.
-// Supports tool calling: OpenAI tools -> Claude tools, tool_calls -> tool_use, tool messages -> tool_result.
-// Supports reasoning/thinking: OpenAI reasoning_effort -> Claude thinking parameter.
-func ConvertOpenAIRequestToKiro(modelName string, inputRawJSON []byte, stream bool) []byte {
-	rawJSON := bytes.Clone(inputRawJSON)
-	root := gjson.ParseBytes(rawJSON)
-
-	// Build Claude-compatible request
-	out := `{"model":"","max_tokens":32000,"messages":[]}`
-
-	// Set model
-	out, _ = sjson.Set(out, "model", modelName)
-
-	// Copy max_tokens if present
-	if v := root.Get("max_tokens"); v.Exists() {
-		out, _ = sjson.Set(out, "max_tokens", v.Int())
-	}
-
-	// Copy temperature if present
-	if v := root.Get("temperature"); v.Exists() {
-		out, _ = sjson.Set(out, "temperature", v.Float())
-	}
-
-	// Copy top_p if present
-	if v := root.Get("top_p"); v.Exists() {
-		out, _ = sjson.Set(out, "top_p", v.Float())
-	}
-
-	// Handle OpenAI reasoning_effort parameter -> Claude thinking parameter
-	// OpenAI format: {"reasoning_effort": "low"|"medium"|"high"}
-	// Claude format: {"thinking": {"type": "enabled", "budget_tokens": N}}
-	if v := root.Get("reasoning_effort"); v.Exists() {
-		effort := v.String()
-		if budget, ok := reasoningEffortToBudget[effort]; ok {
-			thinking := map[string]interface{}{
-				"type":          "enabled",
-				"budget_tokens": budget,
-			}
-			out, _ = sjson.Set(out, "thinking", thinking)
-		}
-	}
-
-	// Also support direct thinking parameter passthrough (for Claude API compatibility)
-	// Claude format: {"thinking": {"type": "enabled", "budget_tokens": N}}
-	if v := root.Get("thinking"); v.Exists() && v.IsObject() {
-		out, _ = sjson.Set(out, "thinking", v.Value())
-	}
-
-	// Convert OpenAI tools to Claude tools format
-	if tools := root.Get("tools"); tools.Exists() && tools.IsArray() {
-		claudeTools := make([]interface{}, 0)
-		for _, tool := range tools.Array() {
-			if tool.Get("type").String() == "function" {
-				fn := tool.Get("function")
-				claudeTool := map[string]interface{}{
-					"name":        fn.Get("name").String(),
-					"description": fn.Get("description").String(),
-				}
-				// Convert parameters to input_schema
-				if params := fn.Get("parameters"); params.Exists() {
-					claudeTool["input_schema"] = params.Value()
-				} else {
-					claudeTool["input_schema"] = map[string]interface{}{
-						"type":       "object",
-						"properties": map[string]interface{}{},
-					}
-				}
-				claudeTools = append(claudeTools, claudeTool)
-			}
-		}
-		if len(claudeTools) > 0 {
-			out, _ = sjson.Set(out, "tools", claudeTools)
-		}
-	}
-
-	// Process messages
-	messages := root.Get("messages")
-	if messages.Exists() && messages.IsArray() {
-		claudeMessages := make([]interface{}, 0)
-		var systemPrompt string
-		
-		// Track pending tool results to merge with next user message
-		var pendingToolResults []map[string]interface{}
-
-		for _, msg := range messages.Array() {
-			role := msg.Get("role").String()
-			content := msg.Get("content")
-
-			if role == "system" {
-				// Extract system message
-				if content.IsArray() {
-					for _, part := range content.Array() {
-						if part.Get("type").String() == "text" {
-							systemPrompt += part.Get("text").String() + "\n"
-						}
-					}
-				} else {
-					systemPrompt = content.String()
-				}
-				continue
-			}
-
-			if role == "tool" {
-				// OpenAI tool message -> Claude tool_result content block
-				toolCallID := msg.Get("tool_call_id").String()
-				toolContent := content.String()
-				
-				toolResult := map[string]interface{}{
-					"type":        "tool_result",
-					"tool_use_id": toolCallID,
-				}
-				
-				// Handle content - can be string or structured
-				if content.IsArray() {
-					contentParts := make([]interface{}, 0)
-					for _, part := range content.Array() {
-						if part.Get("type").String() == "text" {
-							contentParts = append(contentParts, map[string]interface{}{
-								"type": "text",
-								"text": part.Get("text").String(),
-							})
-						}
-					}
-					toolResult["content"] = contentParts
-				} else {
-					toolResult["content"] = toolContent
-				}
-				
-				pendingToolResults = append(pendingToolResults, toolResult)
-				continue
-			}
-
-			claudeMsg := map[string]interface{}{
-				"role": role,
-			}
-
-			// Handle assistant messages with tool_calls
-			if role == "assistant" && msg.Get("tool_calls").Exists() {
-				contentParts := make([]interface{}, 0)
-				
-				// Add text content if present
-				if content.Exists() && content.String() != "" {
-					contentParts = append(contentParts, map[string]interface{}{
-						"type": "text",
-						"text": content.String(),
-					})
-				}
-				
-				// Convert tool_calls to tool_use blocks
-				for _, toolCall := range msg.Get("tool_calls").Array() {
-					toolUseID := toolCall.Get("id").String()
-					fnName := toolCall.Get("function.name").String()
-					fnArgs := toolCall.Get("function.arguments").String()
-					
-					// Parse arguments JSON
-					var argsMap map[string]interface{}
-					if err := json.Unmarshal([]byte(fnArgs), &argsMap); err != nil {
-						argsMap = map[string]interface{}{"raw": fnArgs}
-					}
-					
-					contentParts = append(contentParts, map[string]interface{}{
-						"type":  "tool_use",
-						"id":    toolUseID,
-						"name":  fnName,
-						"input": argsMap,
-					})
-				}
-				
-				claudeMsg["content"] = contentParts
-				claudeMessages = append(claudeMessages, claudeMsg)
-				continue
-			}
-
-			// Handle user messages - may need to include pending tool results
-			if role == "user" && len(pendingToolResults) > 0 {
-				contentParts := make([]interface{}, 0)
-				
-				// Add pending tool results first
-				for _, tr := range pendingToolResults {
-					contentParts = append(contentParts, tr)
-				}
-				pendingToolResults = nil
-				
-				// Add user content
-				if content.IsArray() {
-					for _, part := range content.Array() {
-						partType := part.Get("type").String()
-						if partType == "text" {
-							contentParts = append(contentParts, map[string]interface{}{
-								"type": "text",
-								"text": part.Get("text").String(),
-							})
-						} else if partType == "image_url" {
-							imageURL := part.Get("image_url.url").String()
-							
-							// Check if it's base64 format (data:image/png;base64,xxxxx)
-							if strings.HasPrefix(imageURL, "data:") {
-								// Parse data URL format
-								// Format: data:image/png;base64,xxxxx
-								commaIdx := strings.Index(imageURL, ",")
-								if commaIdx != -1 {
-									// Extract media_type (e.g., "image/png")
-									header := imageURL[5:commaIdx] // Remove "data:" prefix
-									mediaType := header
-									if semiIdx := strings.Index(header, ";"); semiIdx != -1 {
-										mediaType = header[:semiIdx]
-									}
-									
-									// Extract base64 data
-									base64Data := imageURL[commaIdx+1:]
-									
-									contentParts = append(contentParts, map[string]interface{}{
-										"type": "image",
-										"source": map[string]interface{}{
-											"type":       "base64",
-											"media_type": mediaType,
-											"data":       base64Data,
-										},
-									})
-								}
-							} else {
-								// Regular URL format - keep original logic
-								contentParts = append(contentParts, map[string]interface{}{
-									"type": "image",
-									"source": map[string]interface{}{
-										"type": "url",
-										"url":  imageURL,
-									},
-								})
-							}
-						}
-					}
-				} else if content.String() != "" {
-					contentParts = append(contentParts, map[string]interface{}{
-						"type": "text",
-						"text": content.String(),
-					})
-				}
-				
-				claudeMsg["content"] = contentParts
-				claudeMessages = append(claudeMessages, claudeMsg)
-				continue
-			}
-
-			// Handle regular content
-			if content.IsArray() {
-				contentParts := make([]interface{}, 0)
-				for _, part := range content.Array() {
-					partType := part.Get("type").String()
-					if partType == "text" {
-						contentParts = append(contentParts, map[string]interface{}{
-							"type": "text",
-							"text": part.Get("text").String(),
-						})
-					} else if partType == "image_url" {
-						imageURL := part.Get("image_url.url").String()
-						
-						// Check if it's base64 format (data:image/png;base64,xxxxx)
-						if strings.HasPrefix(imageURL, "data:") {
-							// Parse data URL format
-							// Format: data:image/png;base64,xxxxx
-							commaIdx := strings.Index(imageURL, ",")
-							if commaIdx != -1 {
-								// Extract media_type (e.g., "image/png")
-								header := imageURL[5:commaIdx] // Remove "data:" prefix
-								mediaType := header
-								if semiIdx := strings.Index(header, ";"); semiIdx != -1 {
-									mediaType = header[:semiIdx]
-								}
-								
-								// Extract base64 data
-								base64Data := imageURL[commaIdx+1:]
-								
-								contentParts = append(contentParts, map[string]interface{}{
-									"type": "image",
-									"source": map[string]interface{}{
-										"type":       "base64",
-										"media_type": mediaType,
-										"data":       base64Data,
-									},
-								})
-							}
-						} else {
-							// Regular URL format - keep original logic
-							contentParts = append(contentParts, map[string]interface{}{
-								"type": "image",
-								"source": map[string]interface{}{
-									"type": "url",
-									"url":  imageURL,
-								},
-							})
-						}
-					}
-				}
-				claudeMsg["content"] = contentParts
-			} else {
-				claudeMsg["content"] = content.String()
-			}
-
-			claudeMessages = append(claudeMessages, claudeMsg)
-		}
-
-		// If there are pending tool results without a following user message,
-		// create a user message with just the tool results
-		if len(pendingToolResults) > 0 {
-			contentParts := make([]interface{}, 0)
-			for _, tr := range pendingToolResults {
-				contentParts = append(contentParts, tr)
-			}
-			claudeMessages = append(claudeMessages, map[string]interface{}{
-				"role":    "user",
-				"content": contentParts,
-			})
-		}
-
-		out, _ = sjson.Set(out, "messages", claudeMessages)
-
-		if systemPrompt != "" {
-			out, _ = sjson.Set(out, "system", systemPrompt)
-		}
-	}
-
-	// Set stream
-	out, _ = sjson.Set(out, "stream", stream)
-
-	return []byte(out)
-}

internal/translator/kiro/openai/chat-completions/kiro_openai_response.go

@@ -1,404 +0,0 @@
-// Package chat_completions provides response translation from Kiro to OpenAI format.
-package chat_completions
-
-import (
-	"context"
-	"encoding/json"
-	"strings"
-	"time"
-
-	"github.com/google/uuid"
-	"github.com/tidwall/gjson"
-)
-
-// ConvertKiroResponseToOpenAI converts Kiro streaming response to OpenAI SSE format.
-// Handles Claude SSE events: content_block_start, content_block_delta, input_json_delta,
-// content_block_stop, message_delta, and message_stop.
-// Input may be in SSE format: "event: xxx\ndata: {...}" or raw JSON.
-func ConvertKiroResponseToOpenAI(ctx context.Context, model string, originalRequest, request, rawResponse []byte, param *any) []string {
-	raw := string(rawResponse)
-	var results []string
-
-	// Handle SSE format: extract JSON from "data: " lines
-	// Input format: "event: message_start\ndata: {...}"
-	lines := strings.Split(raw, "\n")
-	for _, line := range lines {
-		line = strings.TrimSpace(line)
-		if strings.HasPrefix(line, "data: ") {
-			jsonPart := strings.TrimPrefix(line, "data: ")
-			chunks := convertClaudeEventToOpenAI(jsonPart, model)
-			results = append(results, chunks...)
-		} else if strings.HasPrefix(line, "{") {
-			// Raw JSON (backward compatibility)
-			chunks := convertClaudeEventToOpenAI(line, model)
-			results = append(results, chunks...)
-		}
-	}
-
-	return results
-}
-
-// convertClaudeEventToOpenAI converts a single Claude JSON event to OpenAI format
-func convertClaudeEventToOpenAI(jsonStr string, model string) []string {
-	root := gjson.Parse(jsonStr)
-	var results []string
-
-	eventType := root.Get("type").String()
-
-	switch eventType {
-	case "message_start":
-		// Initial message event - emit initial chunk with role
-		response := map[string]interface{}{
-			"id":      "chatcmpl-" + uuid.New().String()[:24],
-			"object":  "chat.completion.chunk",
-			"created": time.Now().Unix(),
-			"model":   model,
-			"choices": []map[string]interface{}{
-				{
-					"index": 0,
-					"delta": map[string]interface{}{
-						"role":    "assistant",
-						"content": "",
-					},
-					"finish_reason": nil,
-				},
-			},
-		}
-		result, _ := json.Marshal(response)
-		results = append(results, string(result))
-		return results
-
-	case "content_block_start":
-		// Start of a content block (text or tool_use)
-		blockType := root.Get("content_block.type").String()
-		index := int(root.Get("index").Int())
-
-		if blockType == "tool_use" {
-			// Start of tool_use block
-			toolUseID := root.Get("content_block.id").String()
-			toolName := root.Get("content_block.name").String()
-
-			toolCall := map[string]interface{}{
-				"index": index,
-				"id":    toolUseID,
-				"type":  "function",
-				"function": map[string]interface{}{
-					"name":      toolName,
-					"arguments": "",
-				},
-			}
-
-			response := map[string]interface{}{
-				"id":      "chatcmpl-" + uuid.New().String()[:24],
-				"object":  "chat.completion.chunk",
-				"created": time.Now().Unix(),
-				"model":   model,
-				"choices": []map[string]interface{}{
-					{
-						"index": 0,
-						"delta": map[string]interface{}{
-							"tool_calls": []map[string]interface{}{toolCall},
-						},
-						"finish_reason": nil,
-					},
-				},
-			}
-			result, _ := json.Marshal(response)
-			results = append(results, string(result))
-		}
-		return results
-
-	case "content_block_delta":
-		index := int(root.Get("index").Int())
-		deltaType := root.Get("delta.type").String()
-
-		if deltaType == "text_delta" {
-			// Text content delta
-			contentDelta := root.Get("delta.text").String()
-			if contentDelta != "" {
-				response := map[string]interface{}{
-					"id":      "chatcmpl-" + uuid.New().String()[:24],
-					"object":  "chat.completion.chunk",
-					"created": time.Now().Unix(),
-					"model":   model,
-					"choices": []map[string]interface{}{
-						{
-							"index": 0,
-							"delta": map[string]interface{}{
-								"content": contentDelta,
-							},
-							"finish_reason": nil,
-						},
-					},
-				}
-				result, _ := json.Marshal(response)
-				results = append(results, string(result))
-			}
-		} else if deltaType == "thinking_delta" {
-			// Thinking/reasoning content delta - convert to OpenAI reasoning_content format
-			thinkingDelta := root.Get("delta.thinking").String()
-			if thinkingDelta != "" {
-				response := map[string]interface{}{
-					"id":      "chatcmpl-" + uuid.New().String()[:24],
-					"object":  "chat.completion.chunk",
-					"created": time.Now().Unix(),
-					"model":   model,
-					"choices": []map[string]interface{}{
-						{
-							"index": 0,
-							"delta": map[string]interface{}{
-								"reasoning_content": thinkingDelta,
-							},
-							"finish_reason": nil,
-						},
-					},
-				}
-				result, _ := json.Marshal(response)
-				results = append(results, string(result))
-			}
-		} else if deltaType == "input_json_delta" {
-			// Tool input delta (streaming arguments)
-			partialJSON := root.Get("delta.partial_json").String()
-			if partialJSON != "" {
-				toolCall := map[string]interface{}{
-					"index": index,
-					"function": map[string]interface{}{
-						"arguments": partialJSON,
-					},
-				}
-
-				response := map[string]interface{}{
-					"id":      "chatcmpl-" + uuid.New().String()[:24],
-					"object":  "chat.completion.chunk",
-					"created": time.Now().Unix(),
-					"model":   model,
-					"choices": []map[string]interface{}{
-						{
-							"index": 0,
-							"delta": map[string]interface{}{
-								"tool_calls": []map[string]interface{}{toolCall},
-							},
-							"finish_reason": nil,
-						},
-					},
-				}
-				result, _ := json.Marshal(response)
-				results = append(results, string(result))
-			}
-		}
-		return results
-
-	case "content_block_stop":
-		// End of content block - no output needed for OpenAI format
-		return results
-
-	case "message_delta":
-		// Final message delta with stop_reason and usage
-		stopReason := root.Get("delta.stop_reason").String()
-		if stopReason != "" {
-			finishReason := "stop"
-			if stopReason == "tool_use" {
-				finishReason = "tool_calls"
-			} else if stopReason == "end_turn" {
-				finishReason = "stop"
-			} else if stopReason == "max_tokens" {
-				finishReason = "length"
-			}
-
-			response := map[string]interface{}{
-				"id":      "chatcmpl-" + uuid.New().String()[:24],
-				"object":  "chat.completion.chunk",
-				"created": time.Now().Unix(),
-				"model":   model,
-				"choices": []map[string]interface{}{
-					{
-						"index":         0,
-						"delta":         map[string]interface{}{},
-						"finish_reason": finishReason,
-					},
-				},
-			}
-
-			// Extract and include usage information from message_delta event
-			usage := root.Get("usage")
-			if usage.Exists() {
-				inputTokens := usage.Get("input_tokens").Int()
-				outputTokens := usage.Get("output_tokens").Int()
-				response["usage"] = map[string]interface{}{
-					"prompt_tokens":     inputTokens,
-					"completion_tokens": outputTokens,
-					"total_tokens":      inputTokens + outputTokens,
-				}
-			}
-
-			result, _ := json.Marshal(response)
-			results = append(results, string(result))
-		}
-		return results
-
-	case "message_stop":
-		// End of message - could emit [DONE] marker
-		return results
-	}
-
-	// Fallback: handle raw content for backward compatibility
-	var contentDelta string
-	if delta := root.Get("delta.text"); delta.Exists() {
-		contentDelta = delta.String()
-	} else if content := root.Get("content"); content.Exists() && root.Get("type").String() == "" {
-		contentDelta = content.String()
-	}
-
-	if contentDelta != "" {
-		response := map[string]interface{}{
-			"id":      "chatcmpl-" + uuid.New().String()[:24],
-			"object":  "chat.completion.chunk",
-			"created": time.Now().Unix(),
-			"model":   model,
-			"choices": []map[string]interface{}{
-				{
-					"index": 0,
-					"delta": map[string]interface{}{
-						"content": contentDelta,
-					},
-					"finish_reason": nil,
-				},
-			},
-		}
-		result, _ := json.Marshal(response)
-		results = append(results, string(result))
-	}
-
-	// Handle tool_use content blocks (Claude format) - fallback
-	toolUses := root.Get("delta.tool_use")
-	if !toolUses.Exists() {
-		toolUses = root.Get("tool_use")
-	}
-	if toolUses.Exists() && toolUses.IsObject() {
-		inputJSON := toolUses.Get("input").String()
-		if inputJSON == "" {
-			if inputObj := toolUses.Get("input"); inputObj.Exists() {
-				inputBytes, _ := json.Marshal(inputObj.Value())
-				inputJSON = string(inputBytes)
-			}
-		}
-
-		toolCall := map[string]interface{}{
-			"index": 0,
-			"id":    toolUses.Get("id").String(),
-			"type":  "function",
-			"function": map[string]interface{}{
-				"name":      toolUses.Get("name").String(),
-				"arguments": inputJSON,
-			},
-		}
-
-		response := map[string]interface{}{
-			"id":      "chatcmpl-" + uuid.New().String()[:24],
-			"object":  "chat.completion.chunk",
-			"created": time.Now().Unix(),
-			"model":   model,
-			"choices": []map[string]interface{}{
-				{
-					"index": 0,
-					"delta": map[string]interface{}{
-						"tool_calls": []map[string]interface{}{toolCall},
-					},
-					"finish_reason": nil,
-				},
-			},
-		}
-		result, _ := json.Marshal(response)
-		results = append(results, string(result))
-	}
-
-	return results
-}
-
-// ConvertKiroResponseToOpenAINonStream converts Kiro non-streaming response to OpenAI format.
-func ConvertKiroResponseToOpenAINonStream(ctx context.Context, model string, originalRequest, request, rawResponse []byte, param *any) string {
-	root := gjson.ParseBytes(rawResponse)
-
-	var content string
-	var reasoningContent string
-	var toolCalls []map[string]interface{}
-
-	contentArray := root.Get("content")
-	if contentArray.IsArray() {
-		for _, item := range contentArray.Array() {
-			itemType := item.Get("type").String()
-			if itemType == "text" {
-				content += item.Get("text").String()
-			} else if itemType == "thinking" {
-				// Extract thinking/reasoning content
-				reasoningContent += item.Get("thinking").String()
-			} else if itemType == "tool_use" {
-				// Convert Claude tool_use to OpenAI tool_calls format
-				inputJSON := item.Get("input").String()
-				if inputJSON == "" {
-					// If input is an object, marshal it
-					if inputObj := item.Get("input"); inputObj.Exists() {
-						inputBytes, _ := json.Marshal(inputObj.Value())
-						inputJSON = string(inputBytes)
-					}
-				}
-				toolCall := map[string]interface{}{
-					"id":   item.Get("id").String(),
-					"type": "function",
-					"function": map[string]interface{}{
-						"name":      item.Get("name").String(),
-						"arguments": inputJSON,
-					},
-				}
-				toolCalls = append(toolCalls, toolCall)
-			}
-		}
-	} else {
-		content = root.Get("content").String()
-	}
-
-	inputTokens := root.Get("usage.input_tokens").Int()
-	outputTokens := root.Get("usage.output_tokens").Int()
-
-	message := map[string]interface{}{
-		"role":    "assistant",
-		"content": content,
-	}
-
-	// Add reasoning_content if present (OpenAI reasoning format)
-	if reasoningContent != "" {
-		message["reasoning_content"] = reasoningContent
-	}
-
-	// Add tool_calls if present
-	if len(toolCalls) > 0 {
-		message["tool_calls"] = toolCalls
-	}
-
-	finishReason := "stop"
-	if len(toolCalls) > 0 {
-		finishReason = "tool_calls"
-	}
-
-	response := map[string]interface{}{
-		"id":      "chatcmpl-" + uuid.New().String()[:24],
-		"object":  "chat.completion",
-		"created": time.Now().Unix(),
-		"model":   model,
-		"choices": []map[string]interface{}{
-			{
-				"index":         0,
-				"message":       message,
-				"finish_reason": finishReason,
-			},
-		},
-		"usage": map[string]interface{}{
-			"prompt_tokens":     inputTokens,
-			"completion_tokens": outputTokens,
-			"total_tokens":      inputTokens + outputTokens,
-		},
-	}
-
-	result, _ := json.Marshal(response)
-	return string(result)
-}

internal/translator/kiro/openai/init.go

@@ -1,4 +1,5 @@
-package chat_completions
+// Package openai provides translation between OpenAI Chat Completions and Kiro formats.
+package openai
 
 import (
 	. "github.com/router-for-me/CLIProxyAPI/v6/internal/constant"
@@ -8,12 +9,12 @@ import (
 
 func init() {
 	translator.Register(
-		OpenAI,
-		Kiro,
+		OpenAI, // source format
+		Kiro,   // target format
 		ConvertOpenAIRequestToKiro,
 		interfaces.TranslateResponse{
-			Stream:    ConvertKiroResponseToOpenAI,
-			NonStream: ConvertKiroResponseToOpenAINonStream,
+			Stream:    ConvertKiroStreamToOpenAI,
+			NonStream: ConvertKiroNonStreamToOpenAI,
 		},
 	)
-}
+}

internal/translator/kiro/openai/kiro_openai.go

@@ -0,0 +1,369 @@
+// Package openai provides translation between OpenAI Chat Completions and Kiro formats.
+// This package enables direct OpenAI → Kiro translation, bypassing the Claude intermediate layer.
+//
+// The Kiro executor generates Claude-compatible SSE format internally, so the streaming response
+// translation converts from Claude SSE format to OpenAI SSE format.
+package openai
+
+import (
+	"bytes"
+	"context"
+	"encoding/json"
+	"strings"
+
+	kirocommon "github.com/router-for-me/CLIProxyAPI/v6/internal/translator/kiro/common"
+	"github.com/router-for-me/CLIProxyAPI/v6/sdk/cliproxy/usage"
+	log "github.com/sirupsen/logrus"
+	"github.com/tidwall/gjson"
+)
+
+// ConvertKiroStreamToOpenAI converts Kiro streaming response to OpenAI format.
+// The Kiro executor emits Claude-compatible SSE events, so this function translates
+// from Claude SSE format to OpenAI SSE format.
+//
+// Claude SSE format:
+//   - event: message_start\ndata: {...}
+//   - event: content_block_start\ndata: {...}
+//   - event: content_block_delta\ndata: {...}
+//   - event: content_block_stop\ndata: {...}
+//   - event: message_delta\ndata: {...}
+//   - event: message_stop\ndata: {...}
+//
+// OpenAI SSE format:
+//   - data: {"id":"...","object":"chat.completion.chunk",...}
+//   - data: [DONE]
+func ConvertKiroStreamToOpenAI(ctx context.Context, model string, originalRequest, request, rawResponse []byte, param *any) []string {
+	// Initialize state if needed
+	if *param == nil {
+		*param = NewOpenAIStreamState(model)
+	}
+	state := (*param).(*OpenAIStreamState)
+
+	// Parse the Claude SSE event
+	responseStr := string(rawResponse)
+
+	// Handle raw event format (event: xxx\ndata: {...})
+	var eventType string
+	var eventData string
+
+	if strings.HasPrefix(responseStr, "event:") {
+		// Parse event type and data
+		lines := strings.SplitN(responseStr, "\n", 2)
+		if len(lines) >= 1 {
+			eventType = strings.TrimSpace(strings.TrimPrefix(lines[0], "event:"))
+		}
+		if len(lines) >= 2 && strings.HasPrefix(lines[1], "data:") {
+			eventData = strings.TrimSpace(strings.TrimPrefix(lines[1], "data:"))
+		}
+	} else if strings.HasPrefix(responseStr, "data:") {
+		// Just data line
+		eventData = strings.TrimSpace(strings.TrimPrefix(responseStr, "data:"))
+	} else {
+		// Try to parse as raw JSON
+		eventData = strings.TrimSpace(responseStr)
+	}
+
+	if eventData == "" {
+		return []string{}
+	}
+
+	// Parse the event data as JSON
+	eventJSON := gjson.Parse(eventData)
+	if !eventJSON.Exists() {
+		return []string{}
+	}
+
+	// Determine event type from JSON if not already set
+	if eventType == "" {
+		eventType = eventJSON.Get("type").String()
+	}
+
+	var results []string
+
+	switch eventType {
+	case "message_start":
+		// Send first chunk with role
+		firstChunk := BuildOpenAISSEFirstChunk(state)
+		results = append(results, firstChunk)
+
+	case "content_block_start":
+		// Check block type
+		blockType := eventJSON.Get("content_block.type").String()
+		switch blockType {
+		case "text":
+			// Text block starting - nothing to emit yet
+		case "thinking":
+			// Thinking block starting - nothing to emit yet for OpenAI
+		case "tool_use":
+			// Tool use block starting
+			toolUseID := eventJSON.Get("content_block.id").String()
+			toolName := eventJSON.Get("content_block.name").String()
+			chunk := BuildOpenAISSEToolCallStart(state, toolUseID, toolName)
+			results = append(results, chunk)
+			state.ToolCallIndex++
+		}
+
+	case "content_block_delta":
+		deltaType := eventJSON.Get("delta.type").String()
+		switch deltaType {
+		case "text_delta":
+			textDelta := eventJSON.Get("delta.text").String()
+			if textDelta != "" {
+				chunk := BuildOpenAISSETextDelta(state, textDelta)
+				results = append(results, chunk)
+			}
+		case "thinking_delta":
+			// Convert thinking to reasoning_content for o1-style compatibility
+			thinkingDelta := eventJSON.Get("delta.thinking").String()
+			if thinkingDelta != "" {
+				chunk := BuildOpenAISSEReasoningDelta(state, thinkingDelta)
+				results = append(results, chunk)
+			}
+		case "input_json_delta":
+			// Tool call arguments delta
+			partialJSON := eventJSON.Get("delta.partial_json").String()
+			if partialJSON != "" {
+				// Get the tool index from content block index
+				blockIndex := int(eventJSON.Get("index").Int())
+				chunk := BuildOpenAISSEToolCallArgumentsDelta(state, partialJSON, blockIndex-1) // Adjust for 0-based tool index
+				results = append(results, chunk)
+			}
+		}
+
+	case "content_block_stop":
+		// Content block ended - nothing to emit for OpenAI
+
+	case "message_delta":
+		// Message delta with stop_reason
+		stopReason := eventJSON.Get("delta.stop_reason").String()
+		finishReason := mapKiroStopReasonToOpenAI(stopReason)
+		if finishReason != "" {
+			chunk := BuildOpenAISSEFinish(state, finishReason)
+			results = append(results, chunk)
+		}
+
+		// Extract usage if present
+		if eventJSON.Get("usage").Exists() {
+			inputTokens := eventJSON.Get("usage.input_tokens").Int()
+			outputTokens := eventJSON.Get("usage.output_tokens").Int()
+			usageInfo := usage.Detail{
+				InputTokens:  inputTokens,
+				OutputTokens: outputTokens,
+				TotalTokens:  inputTokens + outputTokens,
+			}
+			chunk := BuildOpenAISSEUsage(state, usageInfo)
+			results = append(results, chunk)
+		}
+
+	case "message_stop":
+		// Final event - do NOT emit [DONE] here
+		// The handler layer (openai_handlers.go) will send [DONE] when the stream closes
+		// Emitting [DONE] here would cause duplicate [DONE] markers
+
+	case "ping":
+		// Ping event with usage - optionally emit usage chunk
+		if eventJSON.Get("usage").Exists() {
+			inputTokens := eventJSON.Get("usage.input_tokens").Int()
+			outputTokens := eventJSON.Get("usage.output_tokens").Int()
+			usageInfo := usage.Detail{
+				InputTokens:  inputTokens,
+				OutputTokens: outputTokens,
+				TotalTokens:  inputTokens + outputTokens,
+			}
+			chunk := BuildOpenAISSEUsage(state, usageInfo)
+			results = append(results, chunk)
+		}
+	}
+
+	return results
+}
+
+// ConvertKiroNonStreamToOpenAI converts Kiro non-streaming response to OpenAI format.
+// The Kiro executor returns Claude-compatible JSON responses, so this function translates
+// from Claude format to OpenAI format.
+func ConvertKiroNonStreamToOpenAI(ctx context.Context, model string, originalRequest, request, rawResponse []byte, param *any) string {
+	// Parse the Claude-format response
+	response := gjson.ParseBytes(rawResponse)
+
+	// Extract content
+	var content string
+	var toolUses []KiroToolUse
+	var stopReason string
+
+	// Get stop_reason
+	stopReason = response.Get("stop_reason").String()
+
+	// Process content blocks
+	contentBlocks := response.Get("content")
+	if contentBlocks.IsArray() {
+		for _, block := range contentBlocks.Array() {
+			blockType := block.Get("type").String()
+			switch blockType {
+			case "text":
+				content += block.Get("text").String()
+			case "thinking":
+				// Skip thinking blocks for OpenAI format (or convert to reasoning_content if needed)
+			case "tool_use":
+				toolUseID := block.Get("id").String()
+				toolName := block.Get("name").String()
+				toolInput := block.Get("input")
+
+				var inputMap map[string]interface{}
+				if toolInput.IsObject() {
+					inputMap = make(map[string]interface{})
+					toolInput.ForEach(func(key, value gjson.Result) bool {
+						inputMap[key.String()] = value.Value()
+						return true
+					})
+				}
+
+				toolUses = append(toolUses, KiroToolUse{
+					ToolUseID: toolUseID,
+					Name:      toolName,
+					Input:     inputMap,
+				})
+			}
+		}
+	}
+
+	// Extract usage
+	usageInfo := usage.Detail{
+		InputTokens:  response.Get("usage.input_tokens").Int(),
+		OutputTokens: response.Get("usage.output_tokens").Int(),
+	}
+	usageInfo.TotalTokens = usageInfo.InputTokens + usageInfo.OutputTokens
+
+	// Build OpenAI response
+	openaiResponse := BuildOpenAIResponse(content, toolUses, model, usageInfo, stopReason)
+	return string(openaiResponse)
+}
+
+// ParseClaudeEvent parses a Claude SSE event and returns the event type and data
+func ParseClaudeEvent(rawEvent []byte) (eventType string, eventData []byte) {
+	lines := bytes.Split(rawEvent, []byte("\n"))
+	for _, line := range lines {
+		line = bytes.TrimSpace(line)
+		if bytes.HasPrefix(line, []byte("event:")) {
+			eventType = string(bytes.TrimSpace(bytes.TrimPrefix(line, []byte("event:"))))
+		} else if bytes.HasPrefix(line, []byte("data:")) {
+			eventData = bytes.TrimSpace(bytes.TrimPrefix(line, []byte("data:")))
+		}
+	}
+	return eventType, eventData
+}
+
+// ExtractThinkingFromContent parses content to extract thinking blocks.
+// Returns cleaned content (without thinking tags) and whether thinking was found.
+func ExtractThinkingFromContent(content string) (string, string, bool) {
+	if !strings.Contains(content, kirocommon.ThinkingStartTag) {
+		return content, "", false
+	}
+
+	var cleanedContent strings.Builder
+	var thinkingContent strings.Builder
+	hasThinking := false
+	remaining := content
+
+	for len(remaining) > 0 {
+		startIdx := strings.Index(remaining, kirocommon.ThinkingStartTag)
+		if startIdx == -1 {
+			cleanedContent.WriteString(remaining)
+			break
+		}
+
+		// Add content before thinking tag
+		cleanedContent.WriteString(remaining[:startIdx])
+
+		// Move past opening tag
+		remaining = remaining[startIdx+len(kirocommon.ThinkingStartTag):]
+
+		// Find closing tag
+		endIdx := strings.Index(remaining, kirocommon.ThinkingEndTag)
+		if endIdx == -1 {
+			// No closing tag - treat rest as thinking
+			thinkingContent.WriteString(remaining)
+			hasThinking = true
+			break
+		}
+
+		// Extract thinking content
+		thinkingContent.WriteString(remaining[:endIdx])
+		hasThinking = true
+		remaining = remaining[endIdx+len(kirocommon.ThinkingEndTag):]
+	}
+
+	return strings.TrimSpace(cleanedContent.String()), strings.TrimSpace(thinkingContent.String()), hasThinking
+}
+
+// ConvertOpenAIToolsToKiroFormat is a helper that converts OpenAI tools format to Kiro format
+func ConvertOpenAIToolsToKiroFormat(tools []map[string]interface{}) []KiroToolWrapper {
+	var kiroTools []KiroToolWrapper
+
+	for _, tool := range tools {
+		toolType, _ := tool["type"].(string)
+		if toolType != "function" {
+			continue
+		}
+
+		fn, ok := tool["function"].(map[string]interface{})
+		if !ok {
+			continue
+		}
+
+		name := kirocommon.GetString(fn, "name")
+		description := kirocommon.GetString(fn, "description")
+		parameters := fn["parameters"]
+
+		if name == "" {
+			continue
+		}
+
+		if description == "" {
+			description = "Tool: " + name
+		}
+
+		kiroTools = append(kiroTools, KiroToolWrapper{
+			ToolSpecification: KiroToolSpecification{
+				Name:        name,
+				Description: description,
+				InputSchema: KiroInputSchema{JSON: parameters},
+			},
+		})
+	}
+
+	return kiroTools
+}
+
+// OpenAIStreamParams holds parameters for OpenAI streaming conversion
+type OpenAIStreamParams struct {
+	State            *OpenAIStreamState
+	ThinkingState    *ThinkingTagState
+	ToolCallsEmitted map[string]bool
+}
+
+// NewOpenAIStreamParams creates new streaming parameters
+func NewOpenAIStreamParams(model string) *OpenAIStreamParams {
+	return &OpenAIStreamParams{
+		State:            NewOpenAIStreamState(model),
+		ThinkingState:    NewThinkingTagState(),
+		ToolCallsEmitted: make(map[string]bool),
+	}
+}
+
+// ConvertClaudeToolUseToOpenAI converts a Claude tool_use block to OpenAI tool_calls format
+func ConvertClaudeToolUseToOpenAI(toolUseID, toolName string, input map[string]interface{}) map[string]interface{} {
+	inputJSON, _ := json.Marshal(input)
+	return map[string]interface{}{
+		"id":   toolUseID,
+		"type": "function",
+		"function": map[string]interface{}{
+			"name":      toolName,
+			"arguments": string(inputJSON),
+		},
+	}
+}
+
+// LogStreamEvent logs a streaming event for debugging
+func LogStreamEvent(eventType, data string) {
+	log.Debugf("kiro-openai: stream event type=%s, data_len=%d", eventType, len(data))
+}

internal/translator/kiro/openai/kiro_openai_request.go

@@ -0,0 +1,848 @@
+// Package openai provides request translation from OpenAI Chat Completions to Kiro format.
+// It handles parsing and transforming OpenAI API requests into the Kiro/Amazon Q API format,
+// extracting model information, system instructions, message contents, and tool declarations.
+package openai
+
+import (
+	"encoding/json"
+	"fmt"
+	"strings"
+	"time"
+	"unicode/utf8"
+
+	"github.com/google/uuid"
+	kirocommon "github.com/router-for-me/CLIProxyAPI/v6/internal/translator/kiro/common"
+	log "github.com/sirupsen/logrus"
+	"github.com/tidwall/gjson"
+)
+
+// Kiro API request structs - reuse from kiroclaude package structure
+
+// KiroPayload is the top-level request structure for Kiro API
+type KiroPayload struct {
+	ConversationState KiroConversationState `json:"conversationState"`
+	ProfileArn        string                `json:"profileArn,omitempty"`
+	InferenceConfig   *KiroInferenceConfig  `json:"inferenceConfig,omitempty"`
+}
+
+// KiroInferenceConfig contains inference parameters for the Kiro API.
+type KiroInferenceConfig struct {
+	MaxTokens   int     `json:"maxTokens,omitempty"`
+	Temperature float64 `json:"temperature,omitempty"`
+	TopP        float64 `json:"topP,omitempty"`
+}
+
+// KiroConversationState holds the conversation context
+type KiroConversationState struct {
+	ChatTriggerType string               `json:"chatTriggerType"` // Required: "MANUAL"
+	ConversationID  string               `json:"conversationId"`
+	CurrentMessage  KiroCurrentMessage   `json:"currentMessage"`
+	History         []KiroHistoryMessage `json:"history,omitempty"`
+}
+
+// KiroCurrentMessage wraps the current user message
+type KiroCurrentMessage struct {
+	UserInputMessage KiroUserInputMessage `json:"userInputMessage"`
+}
+
+// KiroHistoryMessage represents a message in the conversation history
+type KiroHistoryMessage struct {
+	UserInputMessage         *KiroUserInputMessage         `json:"userInputMessage,omitempty"`
+	AssistantResponseMessage *KiroAssistantResponseMessage `json:"assistantResponseMessage,omitempty"`
+}
+
+// KiroImage represents an image in Kiro API format
+type KiroImage struct {
+	Format string          `json:"format"`
+	Source KiroImageSource `json:"source"`
+}
+
+// KiroImageSource contains the image data
+type KiroImageSource struct {
+	Bytes string `json:"bytes"` // base64 encoded image data
+}
+
+// KiroUserInputMessage represents a user message
+type KiroUserInputMessage struct {
+	Content                 string                       `json:"content"`
+	ModelID                 string                       `json:"modelId"`
+	Origin                  string                       `json:"origin"`
+	Images                  []KiroImage                  `json:"images,omitempty"`
+	UserInputMessageContext *KiroUserInputMessageContext `json:"userInputMessageContext,omitempty"`
+}
+
+// KiroUserInputMessageContext contains tool-related context
+type KiroUserInputMessageContext struct {
+	ToolResults []KiroToolResult  `json:"toolResults,omitempty"`
+	Tools       []KiroToolWrapper `json:"tools,omitempty"`
+}
+
+// KiroToolResult represents a tool execution result
+type KiroToolResult struct {
+	Content   []KiroTextContent `json:"content"`
+	Status    string            `json:"status"`
+	ToolUseID string            `json:"toolUseId"`
+}
+
+// KiroTextContent represents text content
+type KiroTextContent struct {
+	Text string `json:"text"`
+}
+
+// KiroToolWrapper wraps a tool specification
+type KiroToolWrapper struct {
+	ToolSpecification KiroToolSpecification `json:"toolSpecification"`
+}
+
+// KiroToolSpecification defines a tool's schema
+type KiroToolSpecification struct {
+	Name        string          `json:"name"`
+	Description string          `json:"description"`
+	InputSchema KiroInputSchema `json:"inputSchema"`
+}
+
+// KiroInputSchema wraps the JSON schema for tool input
+type KiroInputSchema struct {
+	JSON interface{} `json:"json"`
+}
+
+// KiroAssistantResponseMessage represents an assistant message
+type KiroAssistantResponseMessage struct {
+	Content  string        `json:"content"`
+	ToolUses []KiroToolUse `json:"toolUses,omitempty"`
+}
+
+// KiroToolUse represents a tool invocation by the assistant
+type KiroToolUse struct {
+	ToolUseID string                 `json:"toolUseId"`
+	Name      string                 `json:"name"`
+	Input     map[string]interface{} `json:"input"`
+}
+
+// ConvertOpenAIRequestToKiro converts an OpenAI Chat Completions request to Kiro format.
+// This is the main entry point for request translation.
+// Note: The actual payload building happens in the executor, this just passes through
+// the OpenAI format which will be converted by BuildKiroPayloadFromOpenAI.
+func ConvertOpenAIRequestToKiro(modelName string, inputRawJSON []byte, stream bool) []byte {
+	// Pass through the OpenAI format - actual conversion happens in BuildKiroPayloadFromOpenAI
+	return inputRawJSON
+}
+
+// BuildKiroPayloadFromOpenAI constructs the Kiro API request payload from OpenAI format.
+// Supports tool calling - tools are passed via userInputMessageContext.
+// origin parameter determines which quota to use: "CLI" for Amazon Q, "AI_EDITOR" for Kiro IDE.
+// isAgentic parameter enables chunked write optimization prompt for -agentic model variants.
+// isChatOnly parameter disables tool calling for -chat model variants (pure conversation mode).
+// Returns the payload and a boolean indicating whether thinking mode was injected.
+func BuildKiroPayloadFromOpenAI(openaiBody []byte, modelID, profileArn, origin string, isAgentic, isChatOnly bool) ([]byte, bool) {
+	// Extract max_tokens for potential use in inferenceConfig
+	// Handle -1 as "use maximum" (Kiro max output is ~32000 tokens)
+	const kiroMaxOutputTokens = 32000
+	var maxTokens int64
+	if mt := gjson.GetBytes(openaiBody, "max_tokens"); mt.Exists() {
+		maxTokens = mt.Int()
+		if maxTokens == -1 {
+			maxTokens = kiroMaxOutputTokens
+			log.Debugf("kiro-openai: max_tokens=-1 converted to %d", kiroMaxOutputTokens)
+		}
+	}
+
+	// Extract temperature if specified
+	var temperature float64
+	var hasTemperature bool
+	if temp := gjson.GetBytes(openaiBody, "temperature"); temp.Exists() {
+		temperature = temp.Float()
+		hasTemperature = true
+	}
+
+	// Extract top_p if specified
+	var topP float64
+	var hasTopP bool
+	if tp := gjson.GetBytes(openaiBody, "top_p"); tp.Exists() {
+		topP = tp.Float()
+		hasTopP = true
+		log.Debugf("kiro-openai: extracted top_p: %.2f", topP)
+	}
+
+	// Normalize origin value for Kiro API compatibility
+	origin = normalizeOrigin(origin)
+	log.Debugf("kiro-openai: normalized origin value: %s", origin)
+
+	messages := gjson.GetBytes(openaiBody, "messages")
+
+	// For chat-only mode, don't include tools
+	var tools gjson.Result
+	if !isChatOnly {
+		tools = gjson.GetBytes(openaiBody, "tools")
+	}
+
+	// Extract system prompt from messages
+	systemPrompt := extractSystemPromptFromOpenAI(messages)
+
+	// Inject timestamp context
+	timestamp := time.Now().Format("2006-01-02 15:04:05 MST")
+	timestampContext := fmt.Sprintf("[Context: Current time is %s]", timestamp)
+	if systemPrompt != "" {
+		systemPrompt = timestampContext + "\n\n" + systemPrompt
+	} else {
+		systemPrompt = timestampContext
+	}
+	log.Debugf("kiro-openai: injected timestamp context: %s", timestamp)
+
+	// Inject agentic optimization prompt for -agentic model variants
+	if isAgentic {
+		if systemPrompt != "" {
+			systemPrompt += "\n"
+		}
+		systemPrompt += kirocommon.KiroAgenticSystemPrompt
+	}
+
+	// Handle tool_choice parameter - Kiro doesn't support it natively, so we inject system prompt hints
+	// OpenAI tool_choice values: "none", "auto", "required", or {"type":"function","function":{"name":"..."}}
+	toolChoiceHint := extractToolChoiceHint(openaiBody)
+	if toolChoiceHint != "" {
+		if systemPrompt != "" {
+			systemPrompt += "\n"
+		}
+		systemPrompt += toolChoiceHint
+		log.Debugf("kiro-openai: injected tool_choice hint into system prompt")
+	}
+
+	// Handle response_format parameter - Kiro doesn't support it natively, so we inject system prompt hints
+	// OpenAI response_format: {"type": "json_object"} or {"type": "json_schema", "json_schema": {...}}
+	responseFormatHint := extractResponseFormatHint(openaiBody)
+	if responseFormatHint != "" {
+		if systemPrompt != "" {
+			systemPrompt += "\n"
+		}
+		systemPrompt += responseFormatHint
+		log.Debugf("kiro-openai: injected response_format hint into system prompt")
+	}
+
+	// Check for thinking mode and inject thinking hint
+	// Supports OpenAI reasoning_effort parameter and model name hints
+	thinkingEnabled, budgetTokens := checkThinkingModeFromOpenAI(openaiBody)
+	if thinkingEnabled {
+		// Adjust budgetTokens based on max_tokens if not explicitly set by reasoning_effort
+		// Use 50% of max_tokens for thinking, with min 8000 and max 24000
+		if maxTokens > 0 && budgetTokens == 16000 { // 16000 is the default, meaning not explicitly set
+			calculatedBudget := maxTokens / 2
+			if calculatedBudget < 8000 {
+				calculatedBudget = 8000
+			}
+			if calculatedBudget > 24000 {
+				calculatedBudget = 24000
+			}
+			budgetTokens = calculatedBudget
+			log.Debugf("kiro-openai: budgetTokens calculated from max_tokens: %d (max_tokens=%d)", budgetTokens, maxTokens)
+		}
+
+		if systemPrompt != "" {
+			systemPrompt += "\n"
+		}
+		dynamicThinkingHint := fmt.Sprintf("<thinking_mode>interleaved</thinking_mode><max_thinking_length>%d</max_thinking_length>", budgetTokens)
+		systemPrompt += dynamicThinkingHint
+		log.Debugf("kiro-openai: injected dynamic thinking hint into system prompt, max_thinking_length: %d", budgetTokens)
+	}
+
+	// Convert OpenAI tools to Kiro format
+	kiroTools := convertOpenAIToolsToKiro(tools)
+
+	// Process messages and build history
+	history, currentUserMsg, currentToolResults := processOpenAIMessages(messages, modelID, origin)
+
+	// Build content with system prompt
+	if currentUserMsg != nil {
+		currentUserMsg.Content = buildFinalContent(currentUserMsg.Content, systemPrompt, currentToolResults)
+
+		// Deduplicate currentToolResults
+		currentToolResults = deduplicateToolResults(currentToolResults)
+
+		// Build userInputMessageContext with tools and tool results
+		if len(kiroTools) > 0 || len(currentToolResults) > 0 {
+			currentUserMsg.UserInputMessageContext = &KiroUserInputMessageContext{
+				Tools:       kiroTools,
+				ToolResults: currentToolResults,
+			}
+		}
+	}
+
+	// Build payload
+	var currentMessage KiroCurrentMessage
+	if currentUserMsg != nil {
+		currentMessage = KiroCurrentMessage{UserInputMessage: *currentUserMsg}
+	} else {
+		fallbackContent := ""
+		if systemPrompt != "" {
+			fallbackContent = "--- SYSTEM PROMPT ---\n" + systemPrompt + "\n--- END SYSTEM PROMPT ---\n"
+		}
+		currentMessage = KiroCurrentMessage{UserInputMessage: KiroUserInputMessage{
+			Content: fallbackContent,
+			ModelID: modelID,
+			Origin:  origin,
+		}}
+	}
+
+	// Build inferenceConfig if we have any inference parameters
+	var inferenceConfig *KiroInferenceConfig
+	if maxTokens > 0 || hasTemperature || hasTopP {
+		inferenceConfig = &KiroInferenceConfig{}
+		if maxTokens > 0 {
+			inferenceConfig.MaxTokens = int(maxTokens)
+		}
+		if hasTemperature {
+			inferenceConfig.Temperature = temperature
+		}
+		if hasTopP {
+			inferenceConfig.TopP = topP
+		}
+	}
+
+	payload := KiroPayload{
+		ConversationState: KiroConversationState{
+			ChatTriggerType: "MANUAL",
+			ConversationID:  uuid.New().String(),
+			CurrentMessage:  currentMessage,
+			History:         history,
+		},
+		ProfileArn:      profileArn,
+		InferenceConfig: inferenceConfig,
+	}
+
+	result, err := json.Marshal(payload)
+	if err != nil {
+		log.Debugf("kiro-openai: failed to marshal payload: %v", err)
+		return nil, false
+	}
+
+	return result, thinkingEnabled
+}
+
+// normalizeOrigin normalizes origin value for Kiro API compatibility
+func normalizeOrigin(origin string) string {
+	switch origin {
+	case "KIRO_CLI":
+		return "CLI"
+	case "KIRO_AI_EDITOR":
+		return "AI_EDITOR"
+	case "AMAZON_Q":
+		return "CLI"
+	case "KIRO_IDE":
+		return "AI_EDITOR"
+	default:
+		return origin
+	}
+}
+
+// extractSystemPromptFromOpenAI extracts system prompt from OpenAI messages
+func extractSystemPromptFromOpenAI(messages gjson.Result) string {
+	if !messages.IsArray() {
+		return ""
+	}
+
+	var systemParts []string
+	for _, msg := range messages.Array() {
+		if msg.Get("role").String() == "system" {
+			content := msg.Get("content")
+			if content.Type == gjson.String {
+				systemParts = append(systemParts, content.String())
+			} else if content.IsArray() {
+				// Handle array content format
+				for _, part := range content.Array() {
+					if part.Get("type").String() == "text" {
+						systemParts = append(systemParts, part.Get("text").String())
+					}
+				}
+			}
+		}
+	}
+
+	return strings.Join(systemParts, "\n")
+}
+
+// shortenToolNameIfNeeded shortens tool names that exceed 64 characters.
+// MCP tools often have long names like "mcp__server-name__tool-name".
+// This preserves the "mcp__" prefix and last segment when possible.
+func shortenToolNameIfNeeded(name string) string {
+	const limit = 64
+	if len(name) <= limit {
+		return name
+	}
+	// For MCP tools, try to preserve prefix and last segment
+	if strings.HasPrefix(name, "mcp__") {
+		idx := strings.LastIndex(name, "__")
+		if idx > 0 {
+			cand := "mcp__" + name[idx+2:]
+			if len(cand) > limit {
+				return cand[:limit]
+			}
+			return cand
+		}
+	}
+	return name[:limit]
+}
+
+// convertOpenAIToolsToKiro converts OpenAI tools to Kiro format
+func convertOpenAIToolsToKiro(tools gjson.Result) []KiroToolWrapper {
+	var kiroTools []KiroToolWrapper
+	if !tools.IsArray() {
+		return kiroTools
+	}
+
+	for _, tool := range tools.Array() {
+		// OpenAI tools have type "function" with function definition inside
+		if tool.Get("type").String() != "function" {
+			continue
+		}
+
+		fn := tool.Get("function")
+		if !fn.Exists() {
+			continue
+		}
+
+		name := fn.Get("name").String()
+		description := fn.Get("description").String()
+		parameters := fn.Get("parameters").Value()
+
+		// Shorten tool name if it exceeds 64 characters (common with MCP tools)
+		originalName := name
+		name = shortenToolNameIfNeeded(name)
+		if name != originalName {
+			log.Debugf("kiro-openai: shortened tool name from '%s' to '%s'", originalName, name)
+		}
+
+		// CRITICAL FIX: Kiro API requires non-empty description
+		if strings.TrimSpace(description) == "" {
+			description = fmt.Sprintf("Tool: %s", name)
+			log.Debugf("kiro-openai: tool '%s' has empty description, using default: %s", name, description)
+		}
+
+		// Truncate long descriptions
+		if len(description) > kirocommon.KiroMaxToolDescLen {
+			truncLen := kirocommon.KiroMaxToolDescLen - 30
+			for truncLen > 0 && !utf8.RuneStart(description[truncLen]) {
+				truncLen--
+			}
+			description = description[:truncLen] + "... (description truncated)"
+		}
+
+		kiroTools = append(kiroTools, KiroToolWrapper{
+			ToolSpecification: KiroToolSpecification{
+				Name:        name,
+				Description: description,
+				InputSchema: KiroInputSchema{JSON: parameters},
+			},
+		})
+	}
+
+	return kiroTools
+}
+
+// processOpenAIMessages processes OpenAI messages and builds Kiro history
+func processOpenAIMessages(messages gjson.Result, modelID, origin string) ([]KiroHistoryMessage, *KiroUserInputMessage, []KiroToolResult) {
+	var history []KiroHistoryMessage
+	var currentUserMsg *KiroUserInputMessage
+	var currentToolResults []KiroToolResult
+
+	if !messages.IsArray() {
+		return history, currentUserMsg, currentToolResults
+	}
+
+	// Merge adjacent messages with the same role
+	messagesArray := kirocommon.MergeAdjacentMessages(messages.Array())
+
+	// Build tool_call_id to name mapping from assistant messages
+	toolCallIDToName := make(map[string]string)
+	for _, msg := range messagesArray {
+		if msg.Get("role").String() == "assistant" {
+			toolCalls := msg.Get("tool_calls")
+			if toolCalls.IsArray() {
+				for _, tc := range toolCalls.Array() {
+					if tc.Get("type").String() == "function" {
+						id := tc.Get("id").String()
+						name := tc.Get("function.name").String()
+						if id != "" && name != "" {
+							toolCallIDToName[id] = name
+						}
+					}
+				}
+			}
+		}
+	}
+
+	for i, msg := range messagesArray {
+		role := msg.Get("role").String()
+		isLastMessage := i == len(messagesArray)-1
+
+		switch role {
+		case "system":
+			// System messages are handled separately via extractSystemPromptFromOpenAI
+			continue
+
+		case "user":
+			userMsg, toolResults := buildUserMessageFromOpenAI(msg, modelID, origin)
+			if isLastMessage {
+				currentUserMsg = &userMsg
+				currentToolResults = toolResults
+			} else {
+				// CRITICAL: Kiro API requires content to be non-empty for history messages
+				if strings.TrimSpace(userMsg.Content) == "" {
+					if len(toolResults) > 0 {
+						userMsg.Content = "Tool results provided."
+					} else {
+						userMsg.Content = "Continue"
+					}
+				}
+				// For history messages, embed tool results in context
+				if len(toolResults) > 0 {
+					userMsg.UserInputMessageContext = &KiroUserInputMessageContext{
+						ToolResults: toolResults,
+					}
+				}
+				history = append(history, KiroHistoryMessage{
+					UserInputMessage: &userMsg,
+				})
+			}
+
+		case "assistant":
+			assistantMsg := buildAssistantMessageFromOpenAI(msg)
+			if isLastMessage {
+				history = append(history, KiroHistoryMessage{
+					AssistantResponseMessage: &assistantMsg,
+				})
+				// Create a "Continue" user message as currentMessage
+				currentUserMsg = &KiroUserInputMessage{
+					Content: "Continue",
+					ModelID: modelID,
+					Origin:  origin,
+				}
+			} else {
+				history = append(history, KiroHistoryMessage{
+					AssistantResponseMessage: &assistantMsg,
+				})
+			}
+
+		case "tool":
+			// Tool messages in OpenAI format provide results for tool_calls
+			// These are typically followed by user or assistant messages
+			// Process them and merge into the next user message's tool results
+			toolCallID := msg.Get("tool_call_id").String()
+			content := msg.Get("content").String()
+
+			if toolCallID != "" {
+				toolResult := KiroToolResult{
+					ToolUseID: toolCallID,
+					Content:   []KiroTextContent{{Text: content}},
+					Status:    "success",
+				}
+				// Tool results should be included in the next user message
+				// For now, collect them and they'll be handled when we build the current message
+				currentToolResults = append(currentToolResults, toolResult)
+			}
+		}
+	}
+
+	return history, currentUserMsg, currentToolResults
+}
+
+// buildUserMessageFromOpenAI builds a user message from OpenAI format and extracts tool results
+func buildUserMessageFromOpenAI(msg gjson.Result, modelID, origin string) (KiroUserInputMessage, []KiroToolResult) {
+	content := msg.Get("content")
+	var contentBuilder strings.Builder
+	var toolResults []KiroToolResult
+	var images []KiroImage
+
+	// Track seen toolCallIds to deduplicate
+	seenToolCallIDs := make(map[string]bool)
+
+	if content.IsArray() {
+		for _, part := range content.Array() {
+			partType := part.Get("type").String()
+			switch partType {
+			case "text":
+				contentBuilder.WriteString(part.Get("text").String())
+			case "image_url":
+				imageURL := part.Get("image_url.url").String()
+				if strings.HasPrefix(imageURL, "data:") {
+					// Parse data URL: data:image/png;base64,xxxxx
+					if idx := strings.Index(imageURL, ";base64,"); idx != -1 {
+						mediaType := imageURL[5:idx] // Skip "data:"
+						data := imageURL[idx+8:]     // Skip ";base64,"
+
+						format := ""
+						if lastSlash := strings.LastIndex(mediaType, "/"); lastSlash != -1 {
+							format = mediaType[lastSlash+1:]
+						}
+
+						if format != "" && data != "" {
+							images = append(images, KiroImage{
+								Format: format,
+								Source: KiroImageSource{
+									Bytes: data,
+								},
+							})
+						}
+					}
+				}
+			}
+		}
+	} else if content.Type == gjson.String {
+		contentBuilder.WriteString(content.String())
+	}
+
+	// Check for tool_calls in the message (shouldn't be in user messages, but handle edge cases)
+	_ = seenToolCallIDs // Used for deduplication if needed
+
+	userMsg := KiroUserInputMessage{
+		Content: contentBuilder.String(),
+		ModelID: modelID,
+		Origin:  origin,
+	}
+
+	if len(images) > 0 {
+		userMsg.Images = images
+	}
+
+	return userMsg, toolResults
+}
+
+// buildAssistantMessageFromOpenAI builds an assistant message from OpenAI format
+func buildAssistantMessageFromOpenAI(msg gjson.Result) KiroAssistantResponseMessage {
+	content := msg.Get("content")
+	var contentBuilder strings.Builder
+	var toolUses []KiroToolUse
+
+	// Handle content
+	if content.Type == gjson.String {
+		contentBuilder.WriteString(content.String())
+	} else if content.IsArray() {
+		for _, part := range content.Array() {
+			if part.Get("type").String() == "text" {
+				contentBuilder.WriteString(part.Get("text").String())
+			}
+		}
+	}
+
+	// Handle tool_calls
+	toolCalls := msg.Get("tool_calls")
+	if toolCalls.IsArray() {
+		for _, tc := range toolCalls.Array() {
+			if tc.Get("type").String() != "function" {
+				continue
+			}
+
+			toolUseID := tc.Get("id").String()
+			toolName := tc.Get("function.name").String()
+			toolArgs := tc.Get("function.arguments").String()
+
+			var inputMap map[string]interface{}
+			if err := json.Unmarshal([]byte(toolArgs), &inputMap); err != nil {
+				log.Debugf("kiro-openai: failed to parse tool arguments: %v", err)
+				inputMap = make(map[string]interface{})
+			}
+
+			toolUses = append(toolUses, KiroToolUse{
+				ToolUseID: toolUseID,
+				Name:      toolName,
+				Input:     inputMap,
+			})
+		}
+	}
+
+	return KiroAssistantResponseMessage{
+		Content:  contentBuilder.String(),
+		ToolUses: toolUses,
+	}
+}
+
+// buildFinalContent builds the final content with system prompt
+func buildFinalContent(content, systemPrompt string, toolResults []KiroToolResult) string {
+	var contentBuilder strings.Builder
+
+	if systemPrompt != "" {
+		contentBuilder.WriteString("--- SYSTEM PROMPT ---\n")
+		contentBuilder.WriteString(systemPrompt)
+		contentBuilder.WriteString("\n--- END SYSTEM PROMPT ---\n\n")
+	}
+
+	contentBuilder.WriteString(content)
+	finalContent := contentBuilder.String()
+
+	// CRITICAL: Kiro API requires content to be non-empty
+	if strings.TrimSpace(finalContent) == "" {
+		if len(toolResults) > 0 {
+			finalContent = "Tool results provided."
+		} else {
+			finalContent = "Continue"
+		}
+		log.Debugf("kiro-openai: content was empty, using default: %s", finalContent)
+	}
+
+	return finalContent
+}
+
+// checkThinkingModeFromOpenAI checks if thinking mode is enabled in the OpenAI request.
+// Returns (thinkingEnabled, budgetTokens).
+// Supports:
+// - reasoning_effort parameter (low/medium/high/auto)
+// - Model name containing "thinking" or "reason"
+// - <thinking_mode> tag in system prompt (AMP/Cursor format)
+func checkThinkingModeFromOpenAI(openaiBody []byte) (bool, int64) {
+	var budgetTokens int64 = 16000 // Default budget
+
+	// Check OpenAI format: reasoning_effort parameter
+	// Valid values: "low", "medium", "high", "auto" (not "none")
+	reasoningEffort := gjson.GetBytes(openaiBody, "reasoning_effort")
+	if reasoningEffort.Exists() {
+		effort := reasoningEffort.String()
+		if effort != "" && effort != "none" {
+			log.Debugf("kiro-openai: thinking mode enabled via reasoning_effort: %s", effort)
+			// Adjust budget based on effort level
+			switch effort {
+			case "low":
+				budgetTokens = 8000
+			case "medium":
+				budgetTokens = 16000
+			case "high":
+				budgetTokens = 32000
+			case "auto":
+				budgetTokens = 16000
+			}
+			return true, budgetTokens
+		}
+	}
+
+	// Check AMP/Cursor format: <thinking_mode>interleaved</thinking_mode> in system prompt
+	bodyStr := string(openaiBody)
+	if strings.Contains(bodyStr, "<thinking_mode>") && strings.Contains(bodyStr, "</thinking_mode>") {
+		startTag := "<thinking_mode>"
+		endTag := "</thinking_mode>"
+		startIdx := strings.Index(bodyStr, startTag)
+		if startIdx >= 0 {
+			startIdx += len(startTag)
+			endIdx := strings.Index(bodyStr[startIdx:], endTag)
+			if endIdx >= 0 {
+				thinkingMode := bodyStr[startIdx : startIdx+endIdx]
+				if thinkingMode == "interleaved" || thinkingMode == "enabled" {
+					log.Debugf("kiro-openai: thinking mode enabled via AMP/Cursor format: %s", thinkingMode)
+					// Try to extract max_thinking_length if present
+					if maxLenStart := strings.Index(bodyStr, "<max_thinking_length>"); maxLenStart >= 0 {
+						maxLenStart += len("<max_thinking_length>")
+						if maxLenEnd := strings.Index(bodyStr[maxLenStart:], "</max_thinking_length>"); maxLenEnd >= 0 {
+							maxLenStr := bodyStr[maxLenStart : maxLenStart+maxLenEnd]
+							if parsed, err := fmt.Sscanf(maxLenStr, "%d", &budgetTokens); err == nil && parsed == 1 {
+								log.Debugf("kiro-openai: extracted max_thinking_length: %d", budgetTokens)
+							}
+						}
+					}
+					return true, budgetTokens
+				}
+			}
+		}
+	}
+
+	// Check model name for thinking hints
+	model := gjson.GetBytes(openaiBody, "model").String()
+	modelLower := strings.ToLower(model)
+	if strings.Contains(modelLower, "thinking") || strings.Contains(modelLower, "-reason") {
+		log.Debugf("kiro-openai: thinking mode enabled via model name hint: %s", model)
+		return true, budgetTokens
+	}
+
+	log.Debugf("kiro-openai: no thinking mode detected in OpenAI request")
+	return false, budgetTokens
+}
+
+// extractToolChoiceHint extracts tool_choice from OpenAI request and returns a system prompt hint.
+// OpenAI tool_choice values:
+// - "none": Don't use any tools
+// - "auto": Model decides (default, no hint needed)
+// - "required": Must use at least one tool
+// - {"type":"function","function":{"name":"..."}} : Must use specific tool
+func extractToolChoiceHint(openaiBody []byte) string {
+	toolChoice := gjson.GetBytes(openaiBody, "tool_choice")
+	if !toolChoice.Exists() {
+		return ""
+	}
+
+	// Handle string values
+	if toolChoice.Type == gjson.String {
+		switch toolChoice.String() {
+		case "none":
+			// Note: When tool_choice is "none", we should ideally not pass tools at all
+			// But since we can't modify tool passing here, we add a strong hint
+			return "[INSTRUCTION: Do NOT use any tools. Respond with text only.]"
+		case "required":
+			return "[INSTRUCTION: You MUST use at least one of the available tools to respond. Do not respond with text only - always make a tool call.]"
+		case "auto":
+			// Default behavior, no hint needed
+			return ""
+		}
+	}
+
+	// Handle object value: {"type":"function","function":{"name":"..."}}
+	if toolChoice.IsObject() {
+		if toolChoice.Get("type").String() == "function" {
+			toolName := toolChoice.Get("function.name").String()
+			if toolName != "" {
+				return fmt.Sprintf("[INSTRUCTION: You MUST use the tool named '%s' to respond. Do not use any other tool or respond with text only.]", toolName)
+			}
+		}
+	}
+
+	return ""
+}
+
+// extractResponseFormatHint extracts response_format from OpenAI request and returns a system prompt hint.
+// OpenAI response_format values:
+// - {"type": "text"}: Default, no hint needed
+// - {"type": "json_object"}: Must respond with valid JSON
+// - {"type": "json_schema", "json_schema": {...}}: Must respond with JSON matching schema
+func extractResponseFormatHint(openaiBody []byte) string {
+	responseFormat := gjson.GetBytes(openaiBody, "response_format")
+	if !responseFormat.Exists() {
+		return ""
+	}
+
+	formatType := responseFormat.Get("type").String()
+	switch formatType {
+	case "json_object":
+		return "[INSTRUCTION: You MUST respond with valid JSON only. Do not include any text before or after the JSON. Do not wrap the JSON in markdown code blocks. Output raw JSON directly.]"
+	case "json_schema":
+		// Extract schema if provided
+		schema := responseFormat.Get("json_schema.schema")
+		if schema.Exists() {
+			schemaStr := schema.Raw
+			// Truncate if too long
+			if len(schemaStr) > 500 {
+				schemaStr = schemaStr[:500] + "..."
+			}
+			return fmt.Sprintf("[INSTRUCTION: You MUST respond with valid JSON that matches this schema: %s. Do not include any text before or after the JSON. Do not wrap the JSON in markdown code blocks. Output raw JSON directly.]", schemaStr)
+		}
+		return "[INSTRUCTION: You MUST respond with valid JSON only. Do not include any text before or after the JSON. Do not wrap the JSON in markdown code blocks. Output raw JSON directly.]"
+	case "text":
+		// Default behavior, no hint needed
+		return ""
+	}
+
+	return ""
+}
+
+// deduplicateToolResults removes duplicate tool results
+func deduplicateToolResults(toolResults []KiroToolResult) []KiroToolResult {
+	if len(toolResults) == 0 {
+		return toolResults
+	}
+
+	seenIDs := make(map[string]bool)
+	unique := make([]KiroToolResult, 0, len(toolResults))
+	for _, tr := range toolResults {
+		if !seenIDs[tr.ToolUseID] {
+			seenIDs[tr.ToolUseID] = true
+			unique = append(unique, tr)
+		} else {
+			log.Debugf("kiro-openai: skipping duplicate toolResult: %s", tr.ToolUseID)
+		}
+	}
+	return unique
+}

internal/translator/kiro/openai/kiro_openai_response.go

@@ -0,0 +1,264 @@
+// Package openai provides response translation from Kiro to OpenAI format.
+// This package handles the conversion of Kiro API responses into OpenAI Chat Completions-compatible
+// JSON format, transforming streaming events and non-streaming responses.
+package openai
+
+import (
+	"encoding/json"
+	"fmt"
+	"sync/atomic"
+	"time"
+
+	"github.com/google/uuid"
+	"github.com/router-for-me/CLIProxyAPI/v6/sdk/cliproxy/usage"
+	log "github.com/sirupsen/logrus"
+)
+
+// functionCallIDCounter provides a process-wide unique counter for function call identifiers.
+var functionCallIDCounter uint64
+
+// BuildOpenAIResponse constructs an OpenAI Chat Completions-compatible response.
+// Supports tool_calls when tools are present in the response.
+// stopReason is passed from upstream; fallback logic applied if empty.
+func BuildOpenAIResponse(content string, toolUses []KiroToolUse, model string, usageInfo usage.Detail, stopReason string) []byte {
+	// Build the message object
+	message := map[string]interface{}{
+		"role":    "assistant",
+		"content": content,
+	}
+
+	// Add tool_calls if present
+	if len(toolUses) > 0 {
+		var toolCalls []map[string]interface{}
+		for i, tu := range toolUses {
+			inputJSON, _ := json.Marshal(tu.Input)
+			toolCalls = append(toolCalls, map[string]interface{}{
+				"id":    tu.ToolUseID,
+				"type":  "function",
+				"index": i,
+				"function": map[string]interface{}{
+					"name":      tu.Name,
+					"arguments": string(inputJSON),
+				},
+			})
+		}
+		message["tool_calls"] = toolCalls
+		// When tool_calls are present, content should be null according to OpenAI spec
+		if content == "" {
+			message["content"] = nil
+		}
+	}
+
+	// Use upstream stopReason; apply fallback logic if not provided
+	finishReason := mapKiroStopReasonToOpenAI(stopReason)
+	if finishReason == "" {
+		finishReason = "stop"
+		if len(toolUses) > 0 {
+			finishReason = "tool_calls"
+		}
+		log.Debugf("kiro-openai: buildOpenAIResponse using fallback finish_reason: %s", finishReason)
+	}
+
+	response := map[string]interface{}{
+		"id":      "chatcmpl-" + uuid.New().String()[:24],
+		"object":  "chat.completion",
+		"created": time.Now().Unix(),
+		"model":   model,
+		"choices": []map[string]interface{}{
+			{
+				"index":         0,
+				"message":       message,
+				"finish_reason": finishReason,
+			},
+		},
+		"usage": map[string]interface{}{
+			"prompt_tokens":     usageInfo.InputTokens,
+			"completion_tokens": usageInfo.OutputTokens,
+			"total_tokens":      usageInfo.InputTokens + usageInfo.OutputTokens,
+		},
+	}
+
+	result, _ := json.Marshal(response)
+	return result
+}
+
+// mapKiroStopReasonToOpenAI converts Kiro/Claude stop_reason to OpenAI finish_reason
+func mapKiroStopReasonToOpenAI(stopReason string) string {
+	switch stopReason {
+	case "end_turn":
+		return "stop"
+	case "stop_sequence":
+		return "stop"
+	case "tool_use":
+		return "tool_calls"
+	case "max_tokens":
+		return "length"
+	case "content_filtered":
+		return "content_filter"
+	default:
+		return stopReason
+	}
+}
+
+// BuildOpenAIStreamChunk constructs an OpenAI Chat Completions streaming chunk.
+// This is the delta format used in streaming responses.
+func BuildOpenAIStreamChunk(model string, deltaContent string, deltaToolCalls []map[string]interface{}, finishReason string, index int) []byte {
+	delta := map[string]interface{}{}
+
+	// First chunk should include role
+	if index == 0 && deltaContent == "" && len(deltaToolCalls) == 0 {
+		delta["role"] = "assistant"
+		delta["content"] = ""
+	} else if deltaContent != "" {
+		delta["content"] = deltaContent
+	}
+
+	// Add tool_calls delta if present
+	if len(deltaToolCalls) > 0 {
+		delta["tool_calls"] = deltaToolCalls
+	}
+
+	choice := map[string]interface{}{
+		"index": 0,
+		"delta": delta,
+	}
+
+	if finishReason != "" {
+		choice["finish_reason"] = finishReason
+	} else {
+		choice["finish_reason"] = nil
+	}
+
+	chunk := map[string]interface{}{
+		"id":      "chatcmpl-" + uuid.New().String()[:12],
+		"object":  "chat.completion.chunk",
+		"created": time.Now().Unix(),
+		"model":   model,
+		"choices": []map[string]interface{}{choice},
+	}
+
+	result, _ := json.Marshal(chunk)
+	return result
+}
+
+// BuildOpenAIStreamChunkWithToolCallStart creates a stream chunk for tool call start
+func BuildOpenAIStreamChunkWithToolCallStart(model string, toolUseID, toolName string, toolIndex int) []byte {
+	toolCall := map[string]interface{}{
+		"index": toolIndex,
+		"id":    toolUseID,
+		"type":  "function",
+		"function": map[string]interface{}{
+			"name":      toolName,
+			"arguments": "",
+		},
+	}
+
+	delta := map[string]interface{}{
+		"tool_calls": []map[string]interface{}{toolCall},
+	}
+
+	choice := map[string]interface{}{
+		"index":         0,
+		"delta":         delta,
+		"finish_reason": nil,
+	}
+
+	chunk := map[string]interface{}{
+		"id":      "chatcmpl-" + uuid.New().String()[:12],
+		"object":  "chat.completion.chunk",
+		"created": time.Now().Unix(),
+		"model":   model,
+		"choices": []map[string]interface{}{choice},
+	}
+
+	result, _ := json.Marshal(chunk)
+	return result
+}
+
+// BuildOpenAIStreamChunkWithToolCallDelta creates a stream chunk for tool call arguments delta
+func BuildOpenAIStreamChunkWithToolCallDelta(model string, argumentsDelta string, toolIndex int) []byte {
+	toolCall := map[string]interface{}{
+		"index": toolIndex,
+		"function": map[string]interface{}{
+			"arguments": argumentsDelta,
+		},
+	}
+
+	delta := map[string]interface{}{
+		"tool_calls": []map[string]interface{}{toolCall},
+	}
+
+	choice := map[string]interface{}{
+		"index":         0,
+		"delta":         delta,
+		"finish_reason": nil,
+	}
+
+	chunk := map[string]interface{}{
+		"id":      "chatcmpl-" + uuid.New().String()[:12],
+		"object":  "chat.completion.chunk",
+		"created": time.Now().Unix(),
+		"model":   model,
+		"choices": []map[string]interface{}{choice},
+	}
+
+	result, _ := json.Marshal(chunk)
+	return result
+}
+
+// BuildOpenAIStreamDoneChunk creates the final [DONE] stream event
+func BuildOpenAIStreamDoneChunk() []byte {
+	return []byte("data: [DONE]")
+}
+
+// BuildOpenAIStreamFinishChunk creates the final chunk with finish_reason
+func BuildOpenAIStreamFinishChunk(model string, finishReason string) []byte {
+	choice := map[string]interface{}{
+		"index":         0,
+		"delta":         map[string]interface{}{},
+		"finish_reason": finishReason,
+	}
+
+	chunk := map[string]interface{}{
+		"id":      "chatcmpl-" + uuid.New().String()[:12],
+		"object":  "chat.completion.chunk",
+		"created": time.Now().Unix(),
+		"model":   model,
+		"choices": []map[string]interface{}{choice},
+	}
+
+	result, _ := json.Marshal(chunk)
+	return result
+}
+
+// BuildOpenAIStreamUsageChunk creates a chunk with usage information (optional, for stream_options.include_usage)
+func BuildOpenAIStreamUsageChunk(model string, usageInfo usage.Detail) []byte {
+	chunk := map[string]interface{}{
+		"id":      "chatcmpl-" + uuid.New().String()[:12],
+		"object":  "chat.completion.chunk",
+		"created": time.Now().Unix(),
+		"model":   model,
+		"choices": []map[string]interface{}{},
+		"usage": map[string]interface{}{
+			"prompt_tokens":     usageInfo.InputTokens,
+			"completion_tokens": usageInfo.OutputTokens,
+			"total_tokens":      usageInfo.InputTokens + usageInfo.OutputTokens,
+		},
+	}
+
+	result, _ := json.Marshal(chunk)
+	return result
+}
+
+// GenerateToolCallID generates a unique tool call ID in OpenAI format
+func GenerateToolCallID(toolName string) string {
+	return fmt.Sprintf("call_%s_%d_%d", toolName[:min(8, len(toolName))], time.Now().UnixNano(), atomic.AddUint64(&functionCallIDCounter, 1))
+}
+
+// min returns the minimum of two integers
+func min(a, b int) int {
+	if a < b {
+		return a
+	}
+	return b
+}

internal/translator/kiro/openai/kiro_openai_stream.go

@@ -0,0 +1,212 @@
+// Package openai provides streaming SSE event building for OpenAI format.
+// This package handles the construction of OpenAI-compatible Server-Sent Events (SSE)
+// for streaming responses from Kiro API.
+package openai
+
+import (
+	"encoding/json"
+	"time"
+
+	"github.com/google/uuid"
+	"github.com/router-for-me/CLIProxyAPI/v6/sdk/cliproxy/usage"
+)
+
+// OpenAIStreamState tracks the state of streaming response conversion
+type OpenAIStreamState struct {
+	ChunkIndex        int
+	ToolCallIndex     int
+	HasSentFirstChunk bool
+	Model             string
+	ResponseID        string
+	Created           int64
+}
+
+// NewOpenAIStreamState creates a new stream state for tracking
+func NewOpenAIStreamState(model string) *OpenAIStreamState {
+	return &OpenAIStreamState{
+		ChunkIndex:        0,
+		ToolCallIndex:     0,
+		HasSentFirstChunk: false,
+		Model:             model,
+		ResponseID:        "chatcmpl-" + uuid.New().String()[:24],
+		Created:           time.Now().Unix(),
+	}
+}
+
+// FormatSSEEvent formats a JSON payload for SSE streaming.
+// Note: This returns raw JSON data without "data:" prefix.
+// The SSE "data:" prefix is added by the Handler layer (e.g., openai_handlers.go)
+// to maintain architectural consistency and avoid double-prefix issues.
+func FormatSSEEvent(data []byte) string {
+	return string(data)
+}
+
+// BuildOpenAISSETextDelta creates an SSE event for text content delta
+func BuildOpenAISSETextDelta(state *OpenAIStreamState, textDelta string) string {
+	delta := map[string]interface{}{
+		"content": textDelta,
+	}
+
+	// Include role in first chunk
+	if !state.HasSentFirstChunk {
+		delta["role"] = "assistant"
+		state.HasSentFirstChunk = true
+	}
+
+	chunk := buildBaseChunk(state, delta, nil)
+	result, _ := json.Marshal(chunk)
+	state.ChunkIndex++
+	return FormatSSEEvent(result)
+}
+
+// BuildOpenAISSEToolCallStart creates an SSE event for tool call start
+func BuildOpenAISSEToolCallStart(state *OpenAIStreamState, toolUseID, toolName string) string {
+	toolCall := map[string]interface{}{
+		"index": state.ToolCallIndex,
+		"id":    toolUseID,
+		"type":  "function",
+		"function": map[string]interface{}{
+			"name":      toolName,
+			"arguments": "",
+		},
+	}
+
+	delta := map[string]interface{}{
+		"tool_calls": []map[string]interface{}{toolCall},
+	}
+
+	// Include role in first chunk if not sent yet
+	if !state.HasSentFirstChunk {
+		delta["role"] = "assistant"
+		state.HasSentFirstChunk = true
+	}
+
+	chunk := buildBaseChunk(state, delta, nil)
+	result, _ := json.Marshal(chunk)
+	state.ChunkIndex++
+	return FormatSSEEvent(result)
+}
+
+// BuildOpenAISSEToolCallArgumentsDelta creates an SSE event for tool call arguments delta
+func BuildOpenAISSEToolCallArgumentsDelta(state *OpenAIStreamState, argumentsDelta string, toolIndex int) string {
+	toolCall := map[string]interface{}{
+		"index": toolIndex,
+		"function": map[string]interface{}{
+			"arguments": argumentsDelta,
+		},
+	}
+
+	delta := map[string]interface{}{
+		"tool_calls": []map[string]interface{}{toolCall},
+	}
+
+	chunk := buildBaseChunk(state, delta, nil)
+	result, _ := json.Marshal(chunk)
+	state.ChunkIndex++
+	return FormatSSEEvent(result)
+}
+
+// BuildOpenAISSEFinish creates an SSE event with finish_reason
+func BuildOpenAISSEFinish(state *OpenAIStreamState, finishReason string) string {
+	chunk := buildBaseChunk(state, map[string]interface{}{}, &finishReason)
+	result, _ := json.Marshal(chunk)
+	state.ChunkIndex++
+	return FormatSSEEvent(result)
+}
+
+// BuildOpenAISSEUsage creates an SSE event with usage information
+func BuildOpenAISSEUsage(state *OpenAIStreamState, usageInfo usage.Detail) string {
+	chunk := map[string]interface{}{
+		"id":      state.ResponseID,
+		"object":  "chat.completion.chunk",
+		"created": state.Created,
+		"model":   state.Model,
+		"choices": []map[string]interface{}{},
+		"usage": map[string]interface{}{
+			"prompt_tokens":     usageInfo.InputTokens,
+			"completion_tokens": usageInfo.OutputTokens,
+			"total_tokens":      usageInfo.InputTokens + usageInfo.OutputTokens,
+		},
+	}
+	result, _ := json.Marshal(chunk)
+	return FormatSSEEvent(result)
+}
+
+// BuildOpenAISSEDone creates the final [DONE] SSE event.
+// Note: This returns raw "[DONE]" without "data:" prefix.
+// The SSE "data:" prefix is added by the Handler layer (e.g., openai_handlers.go)
+// to maintain architectural consistency and avoid double-prefix issues.
+func BuildOpenAISSEDone() string {
+	return "[DONE]"
+}
+
+// buildBaseChunk creates a base chunk structure for streaming
+func buildBaseChunk(state *OpenAIStreamState, delta map[string]interface{}, finishReason *string) map[string]interface{} {
+	choice := map[string]interface{}{
+		"index": 0,
+		"delta": delta,
+	}
+
+	if finishReason != nil {
+		choice["finish_reason"] = *finishReason
+	} else {
+		choice["finish_reason"] = nil
+	}
+
+	return map[string]interface{}{
+		"id":      state.ResponseID,
+		"object":  "chat.completion.chunk",
+		"created": state.Created,
+		"model":   state.Model,
+		"choices": []map[string]interface{}{choice},
+	}
+}
+
+// BuildOpenAISSEReasoningDelta creates an SSE event for reasoning content delta
+// This is used for o1/o3 style models that expose reasoning tokens
+func BuildOpenAISSEReasoningDelta(state *OpenAIStreamState, reasoningDelta string) string {
+	delta := map[string]interface{}{
+		"reasoning_content": reasoningDelta,
+	}
+
+	// Include role in first chunk
+	if !state.HasSentFirstChunk {
+		delta["role"] = "assistant"
+		state.HasSentFirstChunk = true
+	}
+
+	chunk := buildBaseChunk(state, delta, nil)
+	result, _ := json.Marshal(chunk)
+	state.ChunkIndex++
+	return FormatSSEEvent(result)
+}
+
+// BuildOpenAISSEFirstChunk creates the first chunk with role only
+func BuildOpenAISSEFirstChunk(state *OpenAIStreamState) string {
+	delta := map[string]interface{}{
+		"role":    "assistant",
+		"content": "",
+	}
+
+	state.HasSentFirstChunk = true
+	chunk := buildBaseChunk(state, delta, nil)
+	result, _ := json.Marshal(chunk)
+	state.ChunkIndex++
+	return FormatSSEEvent(result)
+}
+
+// ThinkingTagState tracks state for thinking tag detection in streaming
+type ThinkingTagState struct {
+	InThinkingBlock   bool
+	PendingStartChars int
+	PendingEndChars   int
+}
+
+// NewThinkingTagState creates a new thinking tag state
+func NewThinkingTagState() *ThinkingTagState {
+	return &ThinkingTagState{
+		InThinkingBlock:   false,
+		PendingStartChars: 0,
+		PendingEndChars:   0,
+	}
+}

internal/translator/openai/claude/openai_claude_request.go

@@ -10,6 +10,7 @@ import (
 	"encoding/json"
 	"strings"
 
+	"github.com/router-for-me/CLIProxyAPI/v6/internal/util"
 	"github.com/tidwall/gjson"
 	"github.com/tidwall/sjson"
 )
@@ -60,6 +61,18 @@ func ConvertClaudeRequestToOpenAI(modelName string, inputRawJSON []byte, stream
 	// Stream
 	out, _ = sjson.Set(out, "stream", stream)
 
+	// Thinking: Convert Claude thinking.budget_tokens to OpenAI reasoning_effort
+	if thinking := root.Get("thinking"); thinking.Exists() && thinking.IsObject() {
+		if thinkingType := thinking.Get("type"); thinkingType.Exists() && thinkingType.String() == "enabled" {
+			if budgetTokens := thinking.Get("budget_tokens"); budgetTokens.Exists() {
+				budget := int(budgetTokens.Int())
+				if effort, ok := util.OpenAIThinkingBudgetToEffort(modelName, budget); ok && effort != "" {
+					out, _ = sjson.Set(out, "reasoning_effort", effort)
+				}
+			}
+		}
+	}
+
 	// Process messages and system
 	var messagesJSON = "[]"
 

internal/translator/openai/gemini/openai_gemini_request.go

@@ -13,6 +13,7 @@ import (
 	"math/big"
 	"strings"
 
+	"github.com/router-for-me/CLIProxyAPI/v6/internal/util"
 	"github.com/tidwall/gjson"
 	"github.com/tidwall/sjson"
 )
@@ -76,6 +77,17 @@ func ConvertGeminiRequestToOpenAI(modelName string, inputRawJSON []byte, stream
 				out, _ = sjson.Set(out, "stop", stops)
 			}
 		}
+
+		// Convert thinkingBudget to reasoning_effort
+		// Always perform conversion to support allowCompat models that may not be in registry
+		if thinkingConfig := genConfig.Get("thinkingConfig"); thinkingConfig.Exists() && thinkingConfig.IsObject() {
+			if thinkingBudget := thinkingConfig.Get("thinkingBudget"); thinkingBudget.Exists() {
+				budget := int(thinkingBudget.Int())
+				if effort, ok := util.OpenAIThinkingBudgetToEffort(modelName, budget); ok && effort != "" {
+					out, _ = sjson.Set(out, "reasoning_effort", effort)
+				}
+			}
+		}
 	}
 
 	// Stream parameter

internal/translator/openai/openai/responses/openai_openai-responses_request.go

@@ -2,6 +2,7 @@ package responses
 
 import (
 	"bytes"
+	"strings"
 
 	"github.com/tidwall/gjson"
 	"github.com/tidwall/sjson"
@@ -64,7 +65,7 @@ func ConvertOpenAIResponsesRequestToOpenAIChatCompletions(modelName string, inpu
 			}
 
 			switch itemType {
-			case "message":
+			case "message", "":
 				// Handle regular message conversion
 				role := item.Get("role").String()
 				message := `{"role":"","content":""}`
@@ -106,6 +107,8 @@ func ConvertOpenAIResponsesRequestToOpenAIChatCompletions(modelName string, inpu
 					if len(toolCalls) > 0 {
 						message, _ = sjson.Set(message, "tool_calls", toolCalls)
 					}
+				} else if content.Type == gjson.String {
+					message, _ = sjson.Set(message, "content", content.String())
 				}
 
 				out, _ = sjson.SetRaw(out, "messages.-1", message)
@@ -189,23 +192,9 @@ func ConvertOpenAIResponsesRequestToOpenAIChatCompletions(modelName string, inpu
 	}
 
 	if reasoningEffort := root.Get("reasoning.effort"); reasoningEffort.Exists() {
-		switch reasoningEffort.String() {
-		case "none":
-			out, _ = sjson.Set(out, "reasoning_effort", "none")
-		case "auto":
-			out, _ = sjson.Set(out, "reasoning_effort", "auto")
-		case "minimal":
-			out, _ = sjson.Set(out, "reasoning_effort", "low")
-		case "low":
-			out, _ = sjson.Set(out, "reasoning_effort", "low")
-		case "medium":
-			out, _ = sjson.Set(out, "reasoning_effort", "medium")
-		case "high":
-			out, _ = sjson.Set(out, "reasoning_effort", "high")
-		case "xhigh":
-			out, _ = sjson.Set(out, "reasoning_effort", "xhigh")
-		default:
-			out, _ = sjson.Set(out, "reasoning_effort", "auto")
+		effort := strings.ToLower(strings.TrimSpace(reasoningEffort.String()))
+		if effort != "" {
+			out, _ = sjson.Set(out, "reasoning_effort", effort)
 		}
 	}
 

internal/util/claude_thinking.go

@@ -28,6 +28,9 @@ func ApplyClaudeThinkingConfig(body []byte, budget *int) []byte {
 // It uses the unified ResolveThinkingConfigFromMetadata and normalizes the budget.
 // Returns the normalized budget (nil if thinking should not be enabled) and whether it matched.
 func ResolveClaudeThinkingConfig(modelName string, metadata map[string]any) (*int, bool) {
+	if !ModelSupportsThinking(modelName) {
+		return nil, false
+	}
 	budget, include, matched := ResolveThinkingConfigFromMetadata(modelName, metadata)
 	if !matched {
 		return nil, false

internal/util/gemini_thinking.go

@@ -25,9 +25,15 @@ func ApplyGeminiThinkingConfig(body []byte, budget *int, includeThoughts *bool)
 			updated = rewritten
 		}
 	}
-	if includeThoughts != nil {
+	// Default to including thoughts when a budget override is present but no explicit include flag is provided.
+	incl := includeThoughts
+	if incl == nil && budget != nil && *budget != 0 {
+		defaultInclude := true
+		incl = &defaultInclude
+	}
+	if incl != nil {
 		valuePath := "generationConfig.thinkingConfig.include_thoughts"
-		rewritten, err := sjson.SetBytes(updated, valuePath, *includeThoughts)
+		rewritten, err := sjson.SetBytes(updated, valuePath, *incl)
 		if err == nil {
 			updated = rewritten
 		}
@@ -47,9 +53,15 @@ func ApplyGeminiCLIThinkingConfig(body []byte, budget *int, includeThoughts *boo
 			updated = rewritten
 		}
 	}
-	if includeThoughts != nil {
+	// Default to including thoughts when a budget override is present but no explicit include flag is provided.
+	incl := includeThoughts
+	if incl == nil && budget != nil && *budget != 0 {
+		defaultInclude := true
+		incl = &defaultInclude
+	}
+	if incl != nil {
 		valuePath := "request.generationConfig.thinkingConfig.include_thoughts"
-		rewritten, err := sjson.SetBytes(updated, valuePath, *includeThoughts)
+		rewritten, err := sjson.SetBytes(updated, valuePath, *incl)
 		if err == nil {
 			updated = rewritten
 		}
@@ -140,6 +152,71 @@ func NormalizeGeminiCLIThinkingBudget(model string, body []byte) []byte {
 	return updated
 }
 
+// ReasoningEffortBudgetMapping defines the thinkingBudget values for each reasoning effort level.
+var ReasoningEffortBudgetMapping = map[string]int{
+	"none":    0,
+	"auto":    -1,
+	"minimal": 512,
+	"low":     1024,
+	"medium":  8192,
+	"high":    24576,
+	"xhigh":   32768,
+}
+
+// ApplyReasoningEffortToGemini applies OpenAI reasoning_effort to Gemini thinkingConfig
+// for standard Gemini API format (generationConfig.thinkingConfig path).
+// Returns the modified body with thinkingBudget and include_thoughts set.
+func ApplyReasoningEffortToGemini(body []byte, effort string) []byte {
+	normalized := strings.ToLower(strings.TrimSpace(effort))
+	if normalized == "" {
+		return body
+	}
+
+	budgetPath := "generationConfig.thinkingConfig.thinkingBudget"
+	includePath := "generationConfig.thinkingConfig.include_thoughts"
+
+	if normalized == "none" {
+		body, _ = sjson.DeleteBytes(body, "generationConfig.thinkingConfig")
+		return body
+	}
+
+	budget, ok := ReasoningEffortBudgetMapping[normalized]
+	if !ok {
+		return body
+	}
+
+	body, _ = sjson.SetBytes(body, budgetPath, budget)
+	body, _ = sjson.SetBytes(body, includePath, true)
+	return body
+}
+
+// ApplyReasoningEffortToGeminiCLI applies OpenAI reasoning_effort to Gemini CLI thinkingConfig
+// for Gemini CLI API format (request.generationConfig.thinkingConfig path).
+// Returns the modified body with thinkingBudget and include_thoughts set.
+func ApplyReasoningEffortToGeminiCLI(body []byte, effort string) []byte {
+	normalized := strings.ToLower(strings.TrimSpace(effort))
+	if normalized == "" {
+		return body
+	}
+
+	budgetPath := "request.generationConfig.thinkingConfig.thinkingBudget"
+	includePath := "request.generationConfig.thinkingConfig.include_thoughts"
+
+	if normalized == "none" {
+		body, _ = sjson.DeleteBytes(body, "request.generationConfig.thinkingConfig")
+		return body
+	}
+
+	budget, ok := ReasoningEffortBudgetMapping[normalized]
+	if !ok {
+		return body
+	}
+
+	body, _ = sjson.SetBytes(body, budgetPath, budget)
+	body, _ = sjson.SetBytes(body, includePath, true)
+	return body
+}
+
 // ConvertThinkingLevelToBudget checks for "generationConfig.thinkingConfig.thinkingLevel"
 // and converts it to "thinkingBudget".
 // "high" -> 32768

internal/util/openai_thinking.go

@@ -0,0 +1,37 @@
+package util
+
+// OpenAIThinkingBudgetToEffort maps a numeric thinking budget (tokens)
+// into an OpenAI-style reasoning effort level for level-based models.
+//
+// Ranges:
+//   - 0            -> "none"
+//   - -1           -> "auto"
+//   - 1..1024      -> "low"
+//   - 1025..8192   -> "medium"
+//   - 8193..24576  -> "high"
+//   - 24577..      -> highest supported level for the model (defaults to "xhigh")
+//
+// Negative values other than -1 are treated as unsupported.
+func OpenAIThinkingBudgetToEffort(model string, budget int) (string, bool) {
+	switch {
+	case budget == -1:
+		return "auto", true
+	case budget < -1:
+		return "", false
+	case budget == 0:
+		return "none", true
+	case budget > 0 && budget <= 1024:
+		return "low", true
+	case budget <= 8192:
+		return "medium", true
+	case budget <= 24576:
+		return "high", true
+	case budget > 24576:
+		if levels := GetModelThinkingLevels(model); len(levels) > 0 {
+			return levels[len(levels)-1], true
+		}
+		return "xhigh", true
+	default:
+		return "", false
+	}
+}

internal/util/thinking_suffix.go

@@ -163,6 +163,11 @@ func ResolveThinkingConfigFromMetadata(model string, metadata map[string]any) (*
 	if !matched {
 		return nil, nil, false
 	}
+	// Level-based models (OpenAI-style) do not accept numeric thinking budgets in
+	// Claude/Gemini-style protocols, so we don't derive budgets for them here.
+	if ModelUsesThinkingLevels(model) {
+		return nil, nil, false
+	}
 
 	if budget == nil && effort != nil {
 		if derived, ok := ThinkingEffortToBudget(model, *effort); ok {

sdk/api/handlers/claude/code_handlers.go

@@ -7,7 +7,6 @@
 package claude
 
 import (
-	"bufio"
 	"bytes"
 	"compress/gzip"
 	"context"
@@ -219,58 +218,24 @@ func (h *ClaudeCodeAPIHandler) handleStreamingResponse(c *gin.Context, rawJSON [
 }
 
 func (h *ClaudeCodeAPIHandler) forwardClaudeStream(c *gin.Context, flusher http.Flusher, cancel func(error), data <-chan []byte, errs <-chan *interfaces.ErrorMessage) {
-	// v6.2: Immediate flush strategy for SSE streams
-	// SSE requires immediate data delivery to prevent client timeouts.
-	// Previous buffering strategy (16KB buffer, 8KB threshold) caused delays
-	// because SSE events are typically small (< 1KB), leading to client retries.
-	writer := bufio.NewWriterSize(c.Writer, 4*1024) // 4KB buffer (smaller for faster flush)
-	ticker := time.NewTicker(50 * time.Millisecond) // 50ms interval for responsive streaming
-	defer ticker.Stop()
-
-	var chunkIdx int
-
+	// OpenAI-style stream forwarding: write each SSE chunk and flush immediately.
+	// This guarantees clients see incremental output even for small responses.
 	for {
 		select {
 		case <-c.Request.Context().Done():
-			// Context cancelled, flush any remaining data before exit
-			_ = writer.Flush()
 			cancel(c.Request.Context().Err())
 			return
 
-		case <-ticker.C:
-			// Flush any buffered data on timer to ensure responsiveness
-			// For SSE, we flush whenever there's any data to prevent client timeouts
-			if writer.Buffered() > 0 {
-				if err := writer.Flush(); err != nil {
-					// Error flushing, cancel and return
-					cancel(err)
-					return
-				}
-				flusher.Flush() // Also flush the underlying http.ResponseWriter
-			}
-
 		case chunk, ok := <-data:
 			if !ok {
-				// Stream ended, flush remaining data
-				_ = writer.Flush()
 				flusher.Flush()
 				cancel(nil)
 				return
 			}
-
-			// Forward the complete SSE event block directly (already formatted by the translator).
-			// The translator returns a complete SSE-compliant event block, including event:, data:, and separators.
-			// The handler just needs to forward it without reassembly.
 			if len(chunk) > 0 {
-				_, _ = writer.Write(chunk)
-				// Immediately flush for first few chunks to establish connection quickly
-				// This prevents client timeout/retry on slow backends like Kiro
-				if chunkIdx < 3 {
-					_ = writer.Flush()
-					flusher.Flush()
-				}
+				_, _ = c.Writer.Write(chunk)
+				flusher.Flush()
 			}
-			chunkIdx++
 
 		case errMsg, ok := <-errs:
 			if !ok {
@@ -282,21 +247,20 @@ func (h *ClaudeCodeAPIHandler) forwardClaudeStream(c *gin.Context, flusher http.
 					status = errMsg.StatusCode
 				}
 				c.Status(status)
+
 				// An error occurred: emit as a proper SSE error event
 				errorBytes, _ := json.Marshal(h.toClaudeError(errMsg))
-				_, _ = writer.WriteString("event: error\n")
-				_, _ = writer.WriteString("data: ")
-				_, _ = writer.Write(errorBytes)
-				_, _ = writer.WriteString("\n\n")
-				_ = writer.Flush()
+				_, _ = fmt.Fprintf(c.Writer, "event: error\ndata: %s\n\n", errorBytes)
 				flusher.Flush()
 			}
+
 			var execErr error
 			if errMsg != nil {
 				execErr = errMsg.Error
 			}
 			cancel(execErr)
 			return
+		case <-time.After(500 * time.Millisecond):
 		}
 	}
 }

sdk/cliproxy/auth/manager.go

@@ -375,10 +375,19 @@ func (m *Manager) executeWithProvider(ctx context.Context, provider string, req
 		}
 
 		accountType, accountInfo := auth.AccountInfo()
+		proxyInfo := auth.ProxyInfo()
 		if accountType == "api_key" {
-			log.Debugf("Use API key %s for model %s", util.HideAPIKey(accountInfo), req.Model)
+			if proxyInfo != "" {
+				log.Debugf("Use API key %s for model %s %s", util.HideAPIKey(accountInfo), req.Model, proxyInfo)
+			} else {
+				log.Debugf("Use API key %s for model %s", util.HideAPIKey(accountInfo), req.Model)
+			}
 		} else if accountType == "oauth" {
-			log.Debugf("Use OAuth %s for model %s", accountInfo, req.Model)
+			if proxyInfo != "" {
+				log.Debugf("Use OAuth %s for model %s %s", accountInfo, req.Model, proxyInfo)
+			} else {
+				log.Debugf("Use OAuth %s for model %s", accountInfo, req.Model)
+			}
 		}
 
 		tried[auth.ID] = struct{}{}
@@ -423,10 +432,19 @@ func (m *Manager) executeCountWithProvider(ctx context.Context, provider string,
 		}
 
 		accountType, accountInfo := auth.AccountInfo()
+		proxyInfo := auth.ProxyInfo()
 		if accountType == "api_key" {
-			log.Debugf("Use API key %s for model %s", util.HideAPIKey(accountInfo), req.Model)
+			if proxyInfo != "" {
+				log.Debugf("Use API key %s for model %s %s", util.HideAPIKey(accountInfo), req.Model, proxyInfo)
+			} else {
+				log.Debugf("Use API key %s for model %s", util.HideAPIKey(accountInfo), req.Model)
+			}
 		} else if accountType == "oauth" {
-			log.Debugf("Use OAuth %s for model %s", accountInfo, req.Model)
+			if proxyInfo != "" {
+				log.Debugf("Use OAuth %s for model %s %s", accountInfo, req.Model, proxyInfo)
+			} else {
+				log.Debugf("Use OAuth %s for model %s", accountInfo, req.Model)
+			}
 		}
 
 		tried[auth.ID] = struct{}{}
@@ -471,10 +489,19 @@ func (m *Manager) executeStreamWithProvider(ctx context.Context, provider string
 		}
 
 		accountType, accountInfo := auth.AccountInfo()
+		proxyInfo := auth.ProxyInfo()
 		if accountType == "api_key" {
-			log.Debugf("Use API key %s for model %s", util.HideAPIKey(accountInfo), req.Model)
+			if proxyInfo != "" {
+				log.Debugf("Use API key %s for model %s %s", util.HideAPIKey(accountInfo), req.Model, proxyInfo)
+			} else {
+				log.Debugf("Use API key %s for model %s", util.HideAPIKey(accountInfo), req.Model)
+			}
 		} else if accountType == "oauth" {
-			log.Debugf("Use OAuth %s for model %s", accountInfo, req.Model)
+			if proxyInfo != "" {
+				log.Debugf("Use OAuth %s for model %s %s", accountInfo, req.Model, proxyInfo)
+			} else {
+				log.Debugf("Use OAuth %s for model %s", accountInfo, req.Model)
+			}
 		}
 
 		tried[auth.ID] = struct{}{}

sdk/cliproxy/auth/types.go

@@ -157,6 +157,20 @@ func (m *ModelState) Clone() *ModelState {
 	return &copyState
 }
 
+func (a *Auth) ProxyInfo() string {
+	if a == nil {
+		return ""
+	}
+	proxyStr := strings.TrimSpace(a.ProxyURL)
+	if proxyStr == "" {
+		return ""
+	}
+	if idx := strings.Index(proxyStr, "://"); idx > 0 {
+		return "via " + proxyStr[:idx] + " proxy"
+	}
+	return "via proxy"
+}
+
 func (a *Auth) AccountInfo() (string, string) {
 	if a == nil {
 		return "", ""

test/thinking_conversion_test.go

@@ -0,0 +1,760 @@
+package test
+
+import (
+	"fmt"
+	"strings"
+	"testing"
+	"time"
+
+	_ "github.com/router-for-me/CLIProxyAPI/v6/internal/translator"
+
+	"github.com/router-for-me/CLIProxyAPI/v6/internal/registry"
+	"github.com/router-for-me/CLIProxyAPI/v6/internal/runtime/executor"
+	"github.com/router-for-me/CLIProxyAPI/v6/internal/util"
+	sdktranslator "github.com/router-for-me/CLIProxyAPI/v6/sdk/translator"
+	"github.com/tidwall/gjson"
+	"github.com/tidwall/sjson"
+)
+
+// isOpenAICompatModel returns true if the model is configured as an OpenAI-compatible
+// model that should have reasoning effort passed through even if not in registry.
+// This simulates the allowCompat behavior from OpenAICompatExecutor.
+func isOpenAICompatModel(model string) bool {
+	return model == "openai-compat"
+}
+
+// registerCoreModels loads representative models across providers into the registry
+// so NormalizeThinkingBudget and level validation use real ranges.
+func registerCoreModels(t *testing.T) func() {
+	t.Helper()
+	reg := registry.GetGlobalRegistry()
+	uid := fmt.Sprintf("thinking-core-%d", time.Now().UnixNano())
+	reg.RegisterClient(uid+"-gemini", "gemini", registry.GetGeminiModels())
+	reg.RegisterClient(uid+"-claude", "claude", registry.GetClaudeModels())
+	reg.RegisterClient(uid+"-openai", "codex", registry.GetOpenAIModels())
+	reg.RegisterClient(uid+"-qwen", "qwen", registry.GetQwenModels())
+	// Custom openai-compatible model with forced thinking suffix passthrough.
+	// No Thinking field - simulates an external model added via openai-compat
+	// where the registry has no knowledge of its thinking capabilities.
+	// The allowCompat flag should preserve reasoning effort for such models.
+	customOpenAIModels := []*registry.ModelInfo{
+		{
+			ID:          "openai-compat",
+			Object:      "model",
+			Created:     1700000000,
+			OwnedBy:     "custom-provider",
+			Type:        "openai",
+			DisplayName: "OpenAI Compatible Model",
+			Description: "OpenAI-compatible model with forced thinking suffix support",
+		},
+	}
+	reg.RegisterClient(uid+"-custom-openai", "codex", customOpenAIModels)
+	return func() {
+		reg.UnregisterClient(uid + "-gemini")
+		reg.UnregisterClient(uid + "-claude")
+		reg.UnregisterClient(uid + "-openai")
+		reg.UnregisterClient(uid + "-qwen")
+		reg.UnregisterClient(uid + "-custom-openai")
+	}
+}
+
+var (
+	thinkingTestModels = []string{
+		"gpt-5",           // level-based thinking model
+		"gemini-2.5-pro",  // numeric-budget thinking model
+		"qwen3-code-plus", // no thinking support
+		"openai-compat",   // allowCompat=true (OpenAI-compatible channel)
+	}
+	thinkingTestFromProtocols = []string{"openai", "claude", "gemini", "openai-response"}
+	thinkingTestToProtocols   = []string{"gemini", "claude", "openai", "codex"}
+
+	// Numeric budgets and their level equivalents:
+	// -1 -> auto
+	// 0 -> none
+	// 1..1024 -> low
+	// 1025..8192 -> medium
+	// 8193..24576 -> high
+	// >24576 -> model highest level (right-most in Levels)
+	thinkingNumericSamples = []int{-1, 0, 1023, 1025, 8193, 64000}
+
+	// Levels and their numeric equivalents:
+	// auto -> -1
+	// none -> 0
+	// minimal -> 512
+	// low -> 1024
+	// medium -> 8192
+	// high -> 24576
+	// xhigh -> 32768
+	// invalid -> invalid (no mapping)
+	thinkingLevelSamples = []string{"auto", "none", "minimal", "low", "medium", "high", "xhigh", "invalid"}
+)
+
+func buildRawPayload(fromProtocol, modelWithSuffix string) []byte {
+	switch fromProtocol {
+	case "gemini":
+		return []byte(fmt.Sprintf(`{"model":"%s","contents":[{"role":"user","parts":[{"text":"hi"}]}]}`, modelWithSuffix))
+	case "openai-response":
+		return []byte(fmt.Sprintf(`{"model":"%s","input":[{"role":"user","content":[{"type":"text","text":"hi"}]}]}`, modelWithSuffix))
+	default: // openai / claude and other chat-style payloads
+		return []byte(fmt.Sprintf(`{"model":"%s","messages":[{"role":"user","content":"hi"}]}`, modelWithSuffix))
+	}
+}
+
+// normalizeCodexPayload mirrors codex_executor's reasoning + streaming tweaks.
+func normalizeCodexPayload(body []byte, upstreamModel string, allowCompat bool) ([]byte, error) {
+	body = executor.NormalizeThinkingConfig(body, upstreamModel, allowCompat)
+	if err := executor.ValidateThinkingConfig(body, upstreamModel); err != nil {
+		return body, err
+	}
+	body, _ = sjson.SetBytes(body, "model", upstreamModel)
+	body, _ = sjson.SetBytes(body, "stream", true)
+	body, _ = sjson.DeleteBytes(body, "previous_response_id")
+	return body, nil
+}
+
+// buildBodyForProtocol runs a minimal request through the same translation and
+// thinking pipeline used in executors for the given target protocol.
+func buildBodyForProtocol(t *testing.T, fromProtocol, toProtocol, modelWithSuffix string) ([]byte, error) {
+	t.Helper()
+	normalizedModel, metadata := util.NormalizeThinkingModel(modelWithSuffix)
+	upstreamModel := util.ResolveOriginalModel(normalizedModel, metadata)
+	raw := buildRawPayload(fromProtocol, modelWithSuffix)
+	stream := fromProtocol != toProtocol
+
+	body := sdktranslator.TranslateRequest(
+		sdktranslator.FromString(fromProtocol),
+		sdktranslator.FromString(toProtocol),
+		normalizedModel,
+		raw,
+		stream,
+	)
+
+	var err error
+	allowCompat := isOpenAICompatModel(normalizedModel)
+	switch toProtocol {
+	case "gemini":
+		body = executor.ApplyThinkingMetadata(body, metadata, normalizedModel)
+		body = util.ApplyDefaultThinkingIfNeeded(normalizedModel, body)
+		body = util.NormalizeGeminiThinkingBudget(normalizedModel, body)
+		body = util.StripThinkingConfigIfUnsupported(normalizedModel, body)
+	case "claude":
+		if budget, ok := util.ResolveClaudeThinkingConfig(normalizedModel, metadata); ok {
+			body = util.ApplyClaudeThinkingConfig(body, budget)
+		}
+	case "openai":
+		body = executor.ApplyReasoningEffortMetadata(body, metadata, normalizedModel, "reasoning_effort", allowCompat)
+		body = executor.NormalizeThinkingConfig(body, upstreamModel, allowCompat)
+		err = executor.ValidateThinkingConfig(body, upstreamModel)
+	case "codex": // OpenAI responses / codex
+		// Codex does not support allowCompat; always use false.
+		body = executor.ApplyReasoningEffortMetadata(body, metadata, normalizedModel, "reasoning.effort", false)
+		// Mirror CodexExecutor final normalization and model override so tests log the final body.
+		body, err = normalizeCodexPayload(body, upstreamModel, false)
+	default:
+	}
+
+	// Mirror executor behavior: final payload uses the upstream (base) model name.
+	if upstreamModel != "" {
+		body, _ = sjson.SetBytes(body, "model", upstreamModel)
+	}
+
+	// For tests we only keep model + thinking-related fields to avoid noise.
+	body = filterThinkingBody(toProtocol, body, upstreamModel, normalizedModel)
+	return body, err
+}
+
+// filterThinkingBody projects the translated payload down to only model and
+// thinking-related fields for the given target protocol.
+func filterThinkingBody(toProtocol string, body []byte, upstreamModel, normalizedModel string) []byte {
+	if len(body) == 0 {
+		return body
+	}
+	out := []byte(`{}`)
+
+	// Preserve model if present, otherwise fall back to upstream/normalized model.
+	if m := gjson.GetBytes(body, "model"); m.Exists() {
+		out, _ = sjson.SetBytes(out, "model", m.Value())
+	} else if upstreamModel != "" {
+		out, _ = sjson.SetBytes(out, "model", upstreamModel)
+	} else if normalizedModel != "" {
+		out, _ = sjson.SetBytes(out, "model", normalizedModel)
+	}
+
+	switch toProtocol {
+	case "gemini":
+		if tc := gjson.GetBytes(body, "generationConfig.thinkingConfig"); tc.Exists() {
+			out, _ = sjson.SetRawBytes(out, "generationConfig.thinkingConfig", []byte(tc.Raw))
+		}
+	case "claude":
+		if tcfg := gjson.GetBytes(body, "thinking"); tcfg.Exists() {
+			out, _ = sjson.SetRawBytes(out, "thinking", []byte(tcfg.Raw))
+		}
+	case "openai":
+		if re := gjson.GetBytes(body, "reasoning_effort"); re.Exists() {
+			out, _ = sjson.SetBytes(out, "reasoning_effort", re.Value())
+		}
+	case "codex":
+		if re := gjson.GetBytes(body, "reasoning.effort"); re.Exists() {
+			out, _ = sjson.SetBytes(out, "reasoning.effort", re.Value())
+		}
+	}
+	return out
+}
+
+func TestThinkingConversionsAcrossProtocolsAndModels(t *testing.T) {
+	cleanup := registerCoreModels(t)
+	defer cleanup()
+
+	type scenario struct {
+		name        string
+		modelSuffix string
+	}
+
+	numericName := func(budget int) string {
+		if budget < 0 {
+			return "numeric-neg1"
+		}
+		return fmt.Sprintf("numeric-%d", budget)
+	}
+
+	for _, model := range thinkingTestModels {
+		_ = registry.GetGlobalRegistry().GetModelInfo(model)
+
+		for _, from := range thinkingTestFromProtocols {
+			// Scenario selection follows protocol semantics:
+			// - OpenAI-style protocols (openai/openai-response) express thinking as levels.
+			// - Claude/Gemini-style protocols express thinking as numeric budgets.
+			cases := []scenario{
+				{name: "no-suffix", modelSuffix: model},
+			}
+			if from == "openai" || from == "openai-response" {
+				for _, lvl := range thinkingLevelSamples {
+					cases = append(cases, scenario{
+						name:        "level-" + lvl,
+						modelSuffix: fmt.Sprintf("%s(%s)", model, lvl),
+					})
+				}
+			} else { // claude or gemini
+				for _, budget := range thinkingNumericSamples {
+					budget := budget
+					cases = append(cases, scenario{
+						name:        numericName(budget),
+						modelSuffix: fmt.Sprintf("%s(%d)", model, budget),
+					})
+				}
+			}
+
+			for _, to := range thinkingTestToProtocols {
+				if from == to {
+					continue
+				}
+				t.Logf("─────────────────────────────────────────────────────────────────────────────────")
+				t.Logf("  %s -> %s | model: %s", from, to, model)
+				t.Logf("─────────────────────────────────────────────────────────────────────────────────")
+				for _, cs := range cases {
+					from := from
+					to := to
+					cs := cs
+					testName := fmt.Sprintf("%s->%s/%s/%s", from, to, model, cs.name)
+					t.Run(testName, func(t *testing.T) {
+						normalizedModel, metadata := util.NormalizeThinkingModel(cs.modelSuffix)
+						expectPresent, expectValue, expectErr := func() (bool, string, bool) {
+							switch to {
+							case "gemini":
+								budget, include, ok := util.ResolveThinkingConfigFromMetadata(normalizedModel, metadata)
+								if !ok || !util.ModelSupportsThinking(normalizedModel) {
+									return false, "", false
+								}
+								if include != nil && !*include {
+									return false, "", false
+								}
+								if budget == nil {
+									return false, "", false
+								}
+								norm := util.NormalizeThinkingBudget(normalizedModel, *budget)
+								return true, fmt.Sprintf("%d", norm), false
+							case "claude":
+								if !util.ModelSupportsThinking(normalizedModel) {
+									return false, "", false
+								}
+								budget, ok := util.ResolveClaudeThinkingConfig(normalizedModel, metadata)
+								if !ok || budget == nil {
+									return false, "", false
+								}
+								return true, fmt.Sprintf("%d", *budget), false
+							case "openai":
+								allowCompat := isOpenAICompatModel(normalizedModel)
+								if !util.ModelSupportsThinking(normalizedModel) && !allowCompat {
+									return false, "", false
+								}
+								// For allowCompat models, pass through effort directly without validation
+								if allowCompat {
+									effort, ok := util.ReasoningEffortFromMetadata(metadata)
+									if ok && strings.TrimSpace(effort) != "" {
+										return true, strings.ToLower(strings.TrimSpace(effort)), false
+									}
+									// Check numeric budget fallback for allowCompat
+									if budget, _, _, matched := util.ThinkingFromMetadata(metadata); matched && budget != nil {
+										if mapped, okMap := util.OpenAIThinkingBudgetToEffort(normalizedModel, *budget); okMap && mapped != "" {
+											return true, mapped, false
+										}
+									}
+									return false, "", false
+								}
+								if !util.ModelUsesThinkingLevels(normalizedModel) {
+									// Non-levels models don't support effort strings in openai
+									return false, "", false
+								}
+								effort, ok := util.ReasoningEffortFromMetadata(metadata)
+								if !ok || strings.TrimSpace(effort) == "" {
+									if budget, _, _, matched := util.ThinkingFromMetadata(metadata); matched && budget != nil {
+										if mapped, okMap := util.OpenAIThinkingBudgetToEffort(normalizedModel, *budget); okMap {
+											effort = mapped
+											ok = true
+										}
+									}
+								}
+								if !ok || strings.TrimSpace(effort) == "" {
+									return false, "", false
+								}
+								effort = strings.ToLower(strings.TrimSpace(effort))
+								if normalized, okLevel := util.NormalizeReasoningEffortLevel(normalizedModel, effort); okLevel {
+									return true, normalized, false
+								}
+								return false, "", true // validation would fail
+							case "codex":
+								// Codex does not support allowCompat; require thinking-capable level models.
+								if !util.ModelSupportsThinking(normalizedModel) || !util.ModelUsesThinkingLevels(normalizedModel) {
+									return false, "", false
+								}
+								effort, ok := util.ReasoningEffortFromMetadata(metadata)
+								if ok && strings.TrimSpace(effort) != "" {
+									effort = strings.ToLower(strings.TrimSpace(effort))
+									if normalized, okLevel := util.NormalizeReasoningEffortLevel(normalizedModel, effort); okLevel {
+										return true, normalized, false
+									}
+									return false, "", true
+								}
+								if budget, _, _, matched := util.ThinkingFromMetadata(metadata); matched && budget != nil {
+									if mapped, okMap := util.OpenAIThinkingBudgetToEffort(normalizedModel, *budget); okMap && mapped != "" {
+										mapped = strings.ToLower(strings.TrimSpace(mapped))
+										if normalized, okLevel := util.NormalizeReasoningEffortLevel(normalizedModel, mapped); okLevel {
+											return true, normalized, false
+										}
+										return false, "", true
+									}
+								}
+								if from != "openai-response" {
+									// Codex translators default reasoning.effort to "medium" when
+									// no explicit thinking suffix/metadata is provided.
+									return true, "medium", false
+								}
+								return false, "", false
+							default:
+								return false, "", false
+							}
+						}()
+
+						body, err := buildBodyForProtocol(t, from, to, cs.modelSuffix)
+						actualPresent, actualValue := func() (bool, string) {
+							path := ""
+							switch to {
+							case "gemini":
+								path = "generationConfig.thinkingConfig.thinkingBudget"
+							case "claude":
+								path = "thinking.budget_tokens"
+							case "openai":
+								path = "reasoning_effort"
+							case "codex":
+								path = "reasoning.effort"
+							}
+							if path == "" {
+								return false, ""
+							}
+							val := gjson.GetBytes(body, path)
+							if to == "codex" && !val.Exists() {
+								reasoning := gjson.GetBytes(body, "reasoning")
+								if reasoning.Exists() {
+									val = reasoning.Get("effort")
+								}
+							}
+							if !val.Exists() {
+								return false, ""
+							}
+							if val.Type == gjson.Number {
+								return true, fmt.Sprintf("%d", val.Int())
+							}
+							return true, val.String()
+						}()
+
+						t.Logf("from=%s to=%s model=%s suffix=%s present(expect=%v got=%v) value(expect=%s got=%s) err(expect=%v got=%v) body=%s",
+							from, to, model, cs.modelSuffix, expectPresent, actualPresent, expectValue, actualValue, expectErr, err != nil, string(body))
+
+						if expectErr {
+							if err == nil {
+								t.Fatalf("expected validation error but got none, body=%s", string(body))
+							}
+							return
+						}
+						if err != nil {
+							t.Fatalf("unexpected error: %v body=%s", err, string(body))
+						}
+
+						if expectPresent != actualPresent {
+							t.Fatalf("presence mismatch: expect %v got %v body=%s", expectPresent, actualPresent, string(body))
+						}
+						if expectPresent && expectValue != actualValue {
+							t.Fatalf("value mismatch: expect %s got %s body=%s", expectValue, actualValue, string(body))
+						}
+					})
+				}
+			}
+		}
+	}
+}
+
+// buildRawPayloadWithThinking creates a payload with thinking parameters already in the body.
+// This tests the path where thinking comes from the raw payload, not model suffix.
+func buildRawPayloadWithThinking(fromProtocol, model string, thinkingParam any) []byte {
+	switch fromProtocol {
+	case "gemini":
+		base := fmt.Sprintf(`{"model":"%s","contents":[{"role":"user","parts":[{"text":"hi"}]}]}`, model)
+		if budget, ok := thinkingParam.(int); ok {
+			base, _ = sjson.Set(base, "generationConfig.thinkingConfig.thinkingBudget", budget)
+		}
+		return []byte(base)
+	case "openai-response":
+		base := fmt.Sprintf(`{"model":"%s","input":[{"role":"user","content":[{"type":"text","text":"hi"}]}]}`, model)
+		if effort, ok := thinkingParam.(string); ok && effort != "" {
+			base, _ = sjson.Set(base, "reasoning.effort", effort)
+		}
+		return []byte(base)
+	case "openai":
+		base := fmt.Sprintf(`{"model":"%s","messages":[{"role":"user","content":"hi"}]}`, model)
+		if effort, ok := thinkingParam.(string); ok && effort != "" {
+			base, _ = sjson.Set(base, "reasoning_effort", effort)
+		}
+		return []byte(base)
+	case "claude":
+		base := fmt.Sprintf(`{"model":"%s","messages":[{"role":"user","content":"hi"}]}`, model)
+		if budget, ok := thinkingParam.(int); ok {
+			base, _ = sjson.Set(base, "thinking.type", "enabled")
+			base, _ = sjson.Set(base, "thinking.budget_tokens", budget)
+		}
+		return []byte(base)
+	default:
+		return []byte(fmt.Sprintf(`{"model":"%s","messages":[{"role":"user","content":"hi"}]}`, model))
+	}
+}
+
+// buildBodyForProtocolWithRawThinking translates payload with raw thinking params.
+func buildBodyForProtocolWithRawThinking(t *testing.T, fromProtocol, toProtocol, model string, thinkingParam any) ([]byte, error) {
+	t.Helper()
+	raw := buildRawPayloadWithThinking(fromProtocol, model, thinkingParam)
+	stream := fromProtocol != toProtocol
+
+	body := sdktranslator.TranslateRequest(
+		sdktranslator.FromString(fromProtocol),
+		sdktranslator.FromString(toProtocol),
+		model,
+		raw,
+		stream,
+	)
+
+	var err error
+	allowCompat := isOpenAICompatModel(model)
+	switch toProtocol {
+	case "gemini":
+		body = util.ApplyDefaultThinkingIfNeeded(model, body)
+		body = util.NormalizeGeminiThinkingBudget(model, body)
+		body = util.StripThinkingConfigIfUnsupported(model, body)
+	case "claude":
+		// For raw payload, Claude thinking is passed through by translator
+		// No additional processing needed as thinking is already in body
+	case "openai":
+		body = executor.NormalizeThinkingConfig(body, model, allowCompat)
+		err = executor.ValidateThinkingConfig(body, model)
+	case "codex":
+		// Codex does not support allowCompat; always use false.
+		body, err = normalizeCodexPayload(body, model, false)
+	}
+
+	body, _ = sjson.SetBytes(body, "model", model)
+	body = filterThinkingBody(toProtocol, body, model, model)
+	return body, err
+}
+
+func TestRawPayloadThinkingConversions(t *testing.T) {
+	cleanup := registerCoreModels(t)
+	defer cleanup()
+
+	type scenario struct {
+		name          string
+		thinkingParam any // int for budget, string for effort level
+	}
+
+	numericName := func(budget int) string {
+		if budget < 0 {
+			return "budget-neg1"
+		}
+		return fmt.Sprintf("budget-%d", budget)
+	}
+
+	for _, model := range thinkingTestModels {
+		supportsThinking := util.ModelSupportsThinking(model)
+		usesLevels := util.ModelUsesThinkingLevels(model)
+		allowCompat := isOpenAICompatModel(model)
+
+		for _, from := range thinkingTestFromProtocols {
+			var cases []scenario
+			switch from {
+			case "openai", "openai-response":
+				cases = []scenario{
+					{name: "no-thinking", thinkingParam: nil},
+				}
+				for _, lvl := range thinkingLevelSamples {
+					cases = append(cases, scenario{
+						name:          "effort-" + lvl,
+						thinkingParam: lvl,
+					})
+				}
+			case "gemini", "claude":
+				cases = []scenario{
+					{name: "no-thinking", thinkingParam: nil},
+				}
+				for _, budget := range thinkingNumericSamples {
+					budget := budget
+					cases = append(cases, scenario{
+						name:          numericName(budget),
+						thinkingParam: budget,
+					})
+				}
+			}
+
+			for _, to := range thinkingTestToProtocols {
+				if from == to {
+					continue
+				}
+				t.Logf("═══════════════════════════════════════════════════════════════════════════════")
+				t.Logf("  RAW PAYLOAD: %s -> %s | model: %s", from, to, model)
+				t.Logf("═══════════════════════════════════════════════════════════════════════════════")
+
+				for _, cs := range cases {
+					from := from
+					to := to
+					cs := cs
+					testName := fmt.Sprintf("raw/%s->%s/%s/%s", from, to, model, cs.name)
+					t.Run(testName, func(t *testing.T) {
+						expectPresent, expectValue, expectErr := func() (bool, string, bool) {
+							if cs.thinkingParam == nil {
+								if to == "codex" && from != "openai-response" && supportsThinking && usesLevels {
+									// Codex translators default reasoning.effort to "medium" for thinking-capable level models
+									return true, "medium", false
+								}
+								return false, "", false
+							}
+
+							switch to {
+							case "gemini":
+								if !supportsThinking || usesLevels {
+									return false, "", false
+								}
+								// Gemini expects numeric budget (only for non-level models)
+								if budget, ok := cs.thinkingParam.(int); ok {
+									norm := util.NormalizeThinkingBudget(model, budget)
+									return true, fmt.Sprintf("%d", norm), false
+								}
+								// Convert effort level to budget for non-level models only
+								if effort, ok := cs.thinkingParam.(string); ok && effort != "" {
+									// "none" disables thinking - no thinkingBudget in output
+									if strings.ToLower(effort) == "none" {
+										return false, "", false
+									}
+									if budget, okB := util.ThinkingEffortToBudget(model, effort); okB {
+										// ThinkingEffortToBudget already returns normalized budget
+										return true, fmt.Sprintf("%d", budget), false
+									}
+									// Invalid effort does not map to a budget
+									return false, "", false
+								}
+								return false, "", false
+							case "claude":
+								if !supportsThinking || usesLevels {
+									return false, "", false
+								}
+								// Claude expects numeric budget (only for non-level models)
+								if budget, ok := cs.thinkingParam.(int); ok && budget > 0 {
+									norm := util.NormalizeThinkingBudget(model, budget)
+									return true, fmt.Sprintf("%d", norm), false
+								}
+								// Convert effort level to budget for non-level models only
+								if effort, ok := cs.thinkingParam.(string); ok && effort != "" {
+									// "none" and "auto" don't produce budget_tokens
+									lower := strings.ToLower(effort)
+									if lower == "none" || lower == "auto" {
+										return false, "", false
+									}
+									if budget, okB := util.ThinkingEffortToBudget(model, effort); okB {
+										// ThinkingEffortToBudget already returns normalized budget
+										return true, fmt.Sprintf("%d", budget), false
+									}
+									// Invalid effort - claude sets thinking.type:enabled but no budget_tokens
+									return false, "", false
+								}
+								return false, "", false
+							case "openai":
+								if allowCompat {
+									if effort, ok := cs.thinkingParam.(string); ok && strings.TrimSpace(effort) != "" {
+										normalized := strings.ToLower(strings.TrimSpace(effort))
+										return true, normalized, false
+									}
+									if budget, ok := cs.thinkingParam.(int); ok {
+										if mapped, okM := util.OpenAIThinkingBudgetToEffort(model, budget); okM && mapped != "" {
+											return true, mapped, false
+										}
+									}
+									return false, "", false
+								}
+								if !supportsThinking || !usesLevels {
+									return false, "", false
+								}
+								if effort, ok := cs.thinkingParam.(string); ok && effort != "" {
+									if normalized, okN := util.NormalizeReasoningEffortLevel(model, effort); okN {
+										return true, normalized, false
+									}
+									return false, "", true // invalid level
+								}
+								if budget, ok := cs.thinkingParam.(int); ok {
+									if mapped, okM := util.OpenAIThinkingBudgetToEffort(model, budget); okM && mapped != "" {
+										// Check if the mapped effort is valid for this model
+										if _, validLevel := util.NormalizeReasoningEffortLevel(model, mapped); !validLevel {
+											return true, mapped, true // expect validation error
+										}
+										return true, mapped, false
+									}
+								}
+								return false, "", false
+							case "codex":
+								// Codex does not support allowCompat; require thinking-capable level models.
+								if !supportsThinking || !usesLevels {
+									return false, "", false
+								}
+								if effort, ok := cs.thinkingParam.(string); ok && effort != "" {
+									if normalized, okN := util.NormalizeReasoningEffortLevel(model, effort); okN {
+										return true, normalized, false
+									}
+									return false, "", true
+								}
+								if budget, ok := cs.thinkingParam.(int); ok {
+									if mapped, okM := util.OpenAIThinkingBudgetToEffort(model, budget); okM && mapped != "" {
+										// Check if the mapped effort is valid for this model
+										if _, validLevel := util.NormalizeReasoningEffortLevel(model, mapped); !validLevel {
+											return true, mapped, true // expect validation error
+										}
+										return true, mapped, false
+									}
+								}
+								if from != "openai-response" {
+									// Codex translators default reasoning.effort to "medium" for thinking-capable models
+									return true, "medium", false
+								}
+								return false, "", false
+							}
+							return false, "", false
+						}()
+
+						body, err := buildBodyForProtocolWithRawThinking(t, from, to, model, cs.thinkingParam)
+						actualPresent, actualValue := func() (bool, string) {
+							path := ""
+							switch to {
+							case "gemini":
+								path = "generationConfig.thinkingConfig.thinkingBudget"
+							case "claude":
+								path = "thinking.budget_tokens"
+							case "openai":
+								path = "reasoning_effort"
+							case "codex":
+								path = "reasoning.effort"
+							}
+							if path == "" {
+								return false, ""
+							}
+							val := gjson.GetBytes(body, path)
+							if to == "codex" && !val.Exists() {
+								reasoning := gjson.GetBytes(body, "reasoning")
+								if reasoning.Exists() {
+									val = reasoning.Get("effort")
+								}
+							}
+							if !val.Exists() {
+								return false, ""
+							}
+							if val.Type == gjson.Number {
+								return true, fmt.Sprintf("%d", val.Int())
+							}
+							return true, val.String()
+						}()
+
+						t.Logf("from=%s to=%s model=%s param=%v present(expect=%v got=%v) value(expect=%s got=%s) err(expect=%v got=%v) body=%s",
+							from, to, model, cs.thinkingParam, expectPresent, actualPresent, expectValue, actualValue, expectErr, err != nil, string(body))
+
+						if expectErr {
+							if err == nil {
+								t.Fatalf("expected validation error but got none, body=%s", string(body))
+							}
+							return
+						}
+						if err != nil {
+							t.Fatalf("unexpected error: %v body=%s", err, string(body))
+						}
+
+						if expectPresent != actualPresent {
+							t.Fatalf("presence mismatch: expect %v got %v body=%s", expectPresent, actualPresent, string(body))
+						}
+						if expectPresent && expectValue != actualValue {
+							t.Fatalf("value mismatch: expect %s got %s body=%s", expectValue, actualValue, string(body))
+						}
+					})
+				}
+			}
+		}
+	}
+}
+
+func TestOpenAIThinkingBudgetToEffortRanges(t *testing.T) {
+	cleanup := registerCoreModels(t)
+	defer cleanup()
+
+	cases := []struct {
+		name   string
+		model  string
+		budget int
+		want   string
+		ok     bool
+	}{
+		{name: "dynamic-auto", model: "gpt-5", budget: -1, want: "auto", ok: true},
+		{name: "zero-none", model: "gpt-5", budget: 0, want: "none", ok: true},
+		{name: "low-min", model: "gpt-5", budget: 1, want: "low", ok: true},
+		{name: "low-max", model: "gpt-5", budget: 1024, want: "low", ok: true},
+		{name: "medium-min", model: "gpt-5", budget: 1025, want: "medium", ok: true},
+		{name: "medium-max", model: "gpt-5", budget: 8192, want: "medium", ok: true},
+		{name: "high-min", model: "gpt-5", budget: 8193, want: "high", ok: true},
+		{name: "high-max", model: "gpt-5", budget: 24576, want: "high", ok: true},
+		{name: "over-max-clamps-to-highest", model: "gpt-5", budget: 64000, want: "high", ok: true},
+		{name: "over-max-xhigh-model", model: "gpt-5.2", budget: 50000, want: "xhigh", ok: true},
+		{name: "negative-unsupported", model: "gpt-5", budget: -5, want: "", ok: false},
+	}
+
+	for _, cs := range cases {
+		cs := cs
+		t.Run(cs.name, func(t *testing.T) {
+			got, ok := util.OpenAIThinkingBudgetToEffort(cs.model, cs.budget)
+			if ok != cs.ok {
+				t.Fatalf("ok mismatch for model=%s budget=%d: expect %v got %v", cs.model, cs.budget, cs.ok, ok)
+			}
+			if got != cs.want {
+				t.Fatalf("value mismatch for model=%s budget=%d: expect %q got %q", cs.model, cs.budget, cs.want, got)
+			}
+		})
+	}
+}