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 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
Compute a size-reduction based keep ratio and use it to trim
tool descriptions, avoiding forced minimum truncation when the
target size already fits. This aligns compression with actual
payload reduction needs and prevents over-compression.
Remove dead code that was never used:
- toolCallIDToName map: built but never read from
- seenToolCallIDs: declared but never populated, only suppressed with _
Fix three issues in Kiro OpenAI translator that caused "Improperly formed request"
errors when processing LiteLLM-translated requests with tool_use/tool_result:
1. Skip merging tool role messages in MergeAdjacentMessages() to preserve
individual tool_call_id fields
2. Track pendingToolResults and attach to the next user message instead of
only the last message. Create synthetic user message when conversation
ends with tool results.
3. Insert synthetic user message with tool results before assistant messages
to maintain proper alternating user/assistant structure. This fixes the case
where LiteLLM translates Anthropic user messages containing only tool_result
blocks into tool role messages followed by assistant.
Adds unit tests covering all tool result handling scenarios.
- Add --kiro-aws-login flag for AWS Builder ID device code flow
- Add DoKiroAWSLogin function for AWS SSO OIDC authentication
- Complete Kiro integration with AWS, Google OAuth, and social auth
- Add kiro executor, translator, and SDK components
- Update browser support for Kiro authentication flows
