Enforces rigorous, evidence-based verification protocols to ensure code is fully tested and functional before making completion claims or creating pull requests.
This skill implements a deterministic 'trust but verify' framework for AI coding agents, ensuring that no task is marked as finished without empirical proof. It mandates a systematic approach—identifying necessary validation commands, executing fresh tests, and analyzing raw output—to prevent 'hallucinated' success. By removing qualitative assumptions and replacing them with deterministic evidence like exit codes and test pass counts, it guarantees high-quality contributions and prevents broken code from entering the version control history.
Key Features
01Detection of non-committal language (should, probably, seems)
02Automated red-green regression testing patterns
03Deterministic build and linter status validation
0429 GitHub stars
05Mandatory gate function for all completion claims
06Independent verification of delegated agent outputs
Use Cases
01Ensuring zero-error linter and build status before PR creation
02Validating complex bug fixes through strict red-green TDD cycles
03Verifying all functional requirements against a checklist before task handoff