What problem does it solve? AI coding agents often claim work is finished without evidence, leaving broken types, failing tests, and half-implemented features. This Skill enforces a mandatory, evidence-based verification workflow before any task can be reported as complete. ## Core Features & Use Cases - Deliverable Enumeration: Lists every requested item with explicit DONE/INCOMPLETE/NOT STARTED status so nothing is silently dropped. - Evidence-Based Verification: Runs type checks, unit tests, and integration tests per affected repo, requiring actual command output as proof rather than summaries. - Anti-Laziness Scanning: Greps your own diff for TODO, FIXME, placeholder, and stub patterns, plus audits adjacent code for broken imports or missing error handling. - Use Case: After implementing a multi-repo feature touching backend and frontend, run this verification to produce a structured completion report proving types pass, tests are green, and no deferred work remains. ## Quick Start Ask the agent to run the completion verification before reporting the current implementation task as done.