Address actionable GitHub pull request review feedback. Use when the user wants to inspect unresolved review threads, requested changes, or inline review comments on a PR, then implement selected fixes. Use the GitHub app for PR metadata and flat comment reads, and use the bundled GraphQL script via `gh` whenever thread-level state, resolution status, or inline review context matters.
npx skills add https://github.com/openai/plugins --skill gh-address-comments
Use this skill when the user wants to work through requested changes on a GitHub pull request. Use the GitHub app from this plugin for PR metadata and patch context, but treat thread-aware review data as a gh api graphql problem because the connector comment surface is flat and does not preserve full review-thread state.
Run all gh commands with elevated network access. If CLI auth is required, confirm gh auth status first and ask the user to authenticate with gh auth login if it fails.
gh auth status and gh pr view --json number,url to resolve it.scripts/fetch_comments.py workflow whenever the task depends on unresolved review threads, inline review locations, or resolution state. That script fetches reviewThreads, isResolved, isOutdated, and file and line anchors that the connector comment surface does not preserve.gh hits auth or rate-limit issues mid-run, ask the user to re-authenticate and retry.If neither the connector nor gh can resolve the PR cleanly, tell the user whether the blocker is missing repository scope, missing PR context, or CLI authentication, then ask for the missing repo or PR identifier or for a refreshed gh login.
Use when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementation
Use when completing tasks, implementing major features, or before merging to verify work meets requirements
Execute git commit with conventional commit message analysis, intelligent staging, and message generation. Use when user asks to commit changes, create a git commit, or mentions "/commit". Supports: (1) Auto-detecting type and scope from changes, (2) Generating conventional commit messages from diff, (3) Interactive commit with optional type/scope/description overrides, (4) Intelligent file staging for logical grouping
Comprehensive GitHub code review with AI-powered swarm coordination
Behavioral guidelines to reduce common LLM coding mistakes. Use when writing, reviewing, or refactoring code to avoid overcomplication, make surgical changes, surface assumptions, and define verifiable success criteria.
Use this skill to review code. It supports both local changes (staged or working tree) and remote Pull Requests (by ID or URL). It focuses on correctness, maintainability, and adherence to project standards.
Refactor bloated AGENTS.md, CLAUDE.md, or similar agent instruction files to follow progressive disclosure principles. Splits monolithic files into organized, linked documentation.
Create high-quality git commits: review/stage intended changes, split into logical commits, and write clear commit messages (including Conventional Commits). Use when the user asks to commit, craft a commit message, stage changes, or split work into multiple commits.
Take openai/plugins-gh-address-comments from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.