When the Kiro/AWS CodeWhisperer API receives a Write tool request with content
that exceeds transmission limits, it truncates the tool input. This can result in:
- Empty input buffer (no input transmitted at all)
- Missing 'content' field in the parsed JSON
- Incomplete JSON that fails to parse
This fix detects these truncation scenarios and converts them to Bash tool calls
that echo an error message. This allows Claude Code to execute the Bash command,
see the error output, and the agent can then retry with smaller chunks.
Changes:
- kiro_claude_tools.go: Detect three truncation scenarios in ProcessToolUseEvent:
1. Empty input buffer (no input transmitted)
2. JSON parse failure with file_path but no content field
3. Successfully parsed JSON missing content field
When detected, emit a special '__truncated_write__' marker tool use
- kiro_executor.go: Handle '__truncated_write__' markers in streamToChannel:
1. Extract file_path from the marker for context
2. Create a Bash tool_use that echoes an error message
3. Include retry guidance (700-line chunks recommended)
4. Set hasToolUses=true to ensure stop_reason='tool_use' for agent continuation
This ensures the agent continues and can retry with smaller file chunks instead
of failing silently or showing errors to the user.
When using Gemini API format with Antigravity backend, the executor
renames usageMetadata to cpaUsageMetadata in non-terminal chunks.
The Gemini translator was returning this internal field name directly
to clients instead of the standard usageMetadata field.
Add restoreUsageMetadata() to rename cpaUsageMetadata back to
usageMetadata before returning responses to clients.
feat(translator): improve system message handling and content indexing across translators
- Updated logic for processing system messages in `claude`, `gemini`, `gemini-cli`, and `antigravity` translators.
- Introduced indexing for `systemInstruction.parts` to ensure proper ordering and handling of multi-part content.
- Added safeguards for accurate content transformation and serialization.
When tool results are sent back to the model, the system prompt was being
re-injected into the user message content, causing the model to think the
user had pasted the system prompt again. This was especially noticeable
after multiple tool uses.
The fix checks if there is conversation history (len(history) > 0). If so,
it's a subsequent turn and we skip system prompt injection. The system
prompt is only injected on the first turn (len(history) == 0).
This ensures:
- First turn: system prompt is injected
- Tool result turns: system prompt is NOT re-injected
- New conversations: system prompt is injected fresh
- Added conditional logic for Codex instruction injection based on configuration.
- Updated role terminology from "user" to "developer" for better alignment with context.
- Added logic to transform `inputResults` into structured JSON for improved processing.
- Removed redundant `safety_identifier` field in executor payload to streamline requests.
