What problem does it solve? It answers whether a change actually meets its acceptance criteria by gathering real evidence instead of assuming tests or passing CI prove correctness, while clearly labeling what remains unverified. ## Core Features & Use Cases - Scoped validation: Run a targeted check, selected criteria, or a full assessment, with partial results explicitly labeling unchecked requirements. - Surface-aware proof selection: Map each changed surface (source, tests, config, lockfiles, schemas, infrastructure, docs, UI) to its strongest practical evidence using the verification reference. - Visual and UI evidence helpers: Check WCAG contrast ratios, lint spacing values against a scale, capture static HTML renders with headless Chrome, and diff before/after screenshots deterministically. - Honest reporting: Distinguish reproduced baseline failures, introduced regressions, flakes, and unavailable evidence; never edit code, weaken thresholds, or convert missing checks into passes. - Use Case: After implementing a UI change, validate it by running the repo's configured checks, capturing before/after screenshots with shot_diff.mjs, verifying contrast with check_contrast.py, and producing a per-criterion pass/fail/unverified report. ## Quick Start Use the validate-work skill to verify my current changes against the acceptance criteria in the issue and report which requirements pass, fail, or remain unverified.