Analyzes past conversation history to find tool call failure patterns,
correlates each failure with what eventually succeeded, and writes
specific project-level learnings to CLAUDE.md and MEMORY.md.
Key design:
- Success correlation: extracts the diff between failed and successful
inputs as the learning (not generic advice)
- Generic architecture: tool-agnostic ToolCall model with pluggable
Scanner/Writer adapters (Claude Code first, extensible to Cursor/Codex)
- 5 analyzers: Environment, Structure, Commands, Retries, Cross-Session
- Dry-run by default, --apply to write, --all for all projects
Also fixes mypy errors in litellm_callback, asgi, langchain chat_model,
and anthropic provider (AsyncClient typing, ToolCall arg-type, int cast).
