What problem does it solve? Valuable lessons from code reviews often get lost after a PR is merged, causing the same bugs to recur. This Skill closes the feedback loop by mining merged PRs for reviewer findings that the author confirmed as valid, then consolidating them into actionable rules written back into review checklists and implementation pattern files. ## Core Features & Use Cases - Validated Finding Extraction: Scans merged PRs via the GitHub API for review comments the PR author acknowledged with a "Valid." reply, ensuring only confirmed issues are captured. - Pattern Consolidation: Groups recurring findings, generalizes them into actionable rules, and maps each to the right section of core or per-package checklist and pattern files. - Safe Execution Modes: Supports --plan (analysis only), --dry-run (show proposed edits without applying), and full apply mode with user confirmation, plus state tracking via config/state.json to process only new PRs. - Use Case: After a sprint with 15 merged PRs, run the skill to mine review feedback, discover that "missing null-check on API response" appeared 4 times, and add it as a new checklist item so future reviews catch it automatically. ## Quick Start Ask the AI to run the upskill workflow to learn from recent merged PR reviews and update the review checklists with any new validated findings.