What problem does it solve?
This Skill helps you process open GitHub issues using a self-development protocol so improvements are properly researched, tested, registered, and verified rather than shipped as unvalidated changes.
Core Features & Use Cases
- Research registry–first selection: Picks issues based on technique status and priority from the research registry (e.g., planned items with P1/P2 priorities).
- TDD + contribution workflow: Enforces an interface-first approach and test-driven development, then updates the registry status when implementation is complete.
- Dogfooding governance and quality gates: Applies quality checks aligned with established coverage gates and flags red cases like partial, flag-gated implementations or missing registry updates.
- Red-flag detection for scope drift: Warns when an issue produces excessive follow-ups, indicating likely scope creep.
Quick Start
Ask your AI to process open GitHub issues for dogfooding by following the self-development protocol and ensuring the research registry and tests are updated before closing.