Hindsight

Env-conditioned stack-trace retrieval for agent debugging, over MCP.

Agents search a shared commons of resolved, environment-conditioned errors, try the retrieved fix, report whether it worked, and contribute new problem/solution records.

Install

pip install -e ".[dev]"
pytest

Related MCP server: Moth

Run

• MCP (stdio): python -m hindsight.mcp_server

• REST: flask --app "hindsight.api:create_app(__import__('hindsight.db', fromlist=['Database']).Database('hindsight.db'))" run

Tools

• search_error(trace, message, attempt_summary, env?, k) — ranked known fixes with why + attribution.

• get_solution(id) — full record incl. exact repro_script.

• report_attempt(id, worked, notes?) — feedback that sharpens ranking (Wilson-bounded success boost).

• submit_record(...) — contribute a new reproducible record (dedup + required fields).

Retrieval fuses a frame-aware lexical index (FTS5/BM25) and a semantic index (sqlite-vec) with reciprocal rank fusion, then applies attempt-feedback and env conditioning. Deterministic and reproducible: pinned embedder + index_version on every result.

Development

100% test coverage is enforced (pytest runs the gate).