What problem does it solve?
AI coding agents sometimes report that tests passed when no test run actually happened, when the last run failed, or when expected values were quietly rewritten to match a bug. This Skill audits the session's claims against its own local record so you can trust a summary before merging.
Core Features & Use Cases
- Claim Verification: Runs nine deterministic checks comparing what the agent said with what the transcript and git working tree actually show.
- Evidence-Based Findings: Each finding includes a timestamp and the quoted line it came from, classified as CAUGHT or SUSPICIOUS.
- Local and Deterministic: No model calls and nothing leaves the machine; the same session always produces the same verdict.
- Use Case: Before merging a branch, ask whether the tests the agent mentioned really ran, and get a report such as a CAUGHT finding showing the claimed "All 33 tests pass" against a failed vitest run.
Quick Start
Ask the assistant to audit this session and confirm whether the tests you were told about actually ran.