gh-address-comments
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.
Best use case
gh-address-comments is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
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.
Teams using gh-address-comments should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/gh-address-comments/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How gh-address-comments Compares
| Feature / Agent | gh-address-comments | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
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.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# GitHub PR Comment Handler 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. ## Workflow 1. Resolve the PR. - If the user provides a repository and PR number or URL, use that directly. - If the request is about the current branch PR, use local git context plus `gh auth status` and `gh pr view --json number,url` to resolve it. 2. Inspect review context with thread-aware reads. - Use the GitHub app from this plugin to fetch PR metadata and patch context when the repo and PR are known. - Use the bundled `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. - Use connector-only comment reads only for lightweight top-level PR comment summaries. 3. Cluster actionable review threads. - Group comments by file or behavior area. - Separate actionable change requests from informational comments, approvals, already-resolved threads, and duplicates. 4. Confirm scope before editing. - Present numbered actionable threads with a one-line summary of the required change. - If the user did not ask to fix everything, ask which threads to address. - If the user asks to fix everything, interpret that as all unresolved actionable threads and call out anything ambiguous. 5. Implement the selected fixes locally. - Keep each code change traceable back to the thread or feedback cluster it addresses. - If a comment calls for explanation rather than code, draft the response rather than forcing a code change. 6. Summarize the result. - List which threads were addressed, which were intentionally left open, and what tests or checks support the change. ## Write Safety - Do not reply on GitHub, resolve review threads, or submit a review unless the user explicitly asks for that write action. - If review comments conflict with each other or would cause a behavioral regression, surface the tradeoff before making changes. - If a comment is ambiguous, ask for clarification or draft a proposed response instead of guessing. - Do not treat flat PR comments from the connector as a complete representation of review-thread state. - If `gh` hits auth or rate-limit issues mid-run, ask the user to re-authenticate and retry. ## Fallback 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.
Related Skills
workflow
Vercel Workflow DevKit (WDK) expert guidance. Use when building durable workflows, long-running tasks, API routes or agents that need pause/resume, retries, step-based execution, or crash-safe orchestration with Vercel Workflow.
verification
Full-story verification — infers what the user is building, then verifies the complete flow end-to-end: browser → API → data → response. Triggers on dev server start and 'why isn't this working' signals.
vercel-storage
Vercel storage expert guidance — Blob, Edge Config, and Marketplace storage (Neon Postgres, Upstash Redis). Use when choosing, configuring, or using data storage with Vercel applications.
vercel-services
Vercel Services — deploy multiple services within a single Vercel project. Use for monorepo layouts or when combining a backend (Python, Go) with a frontend (Next.js, Vite) in one deployment.
vercel-sandbox
Vercel Sandbox guidance — ephemeral Firecracker microVMs for running untrusted code safely. Supports AI agents, code generation, and experimentation. Use when executing user-generated or AI-generated code in isolation.
vercel-queues
Vercel Queues guidance (public beta) — durable event streaming with topics, consumer groups, retries, and delayed delivery. $0.60/1M ops. Powers Workflow DevKit. Use when building async processing, fan-out patterns, or event-driven architectures.
vercel-functions
Vercel Functions expert guidance — Serverless Functions, Edge Functions, Fluid Compute, streaming, Cron Jobs, and runtime configuration. Use when configuring, debugging, or optimizing server-side code running on Vercel.
vercel-flags
Vercel Flags guidance — feature flags platform with unified dashboard, Flags Explorer, gradual rollouts, A/B testing, and provider adapters. Use when implementing feature flags, experimentation, or staged rollouts.
vercel-firewall
Vercel Firewall and security expert guidance. Use when configuring DDoS protection, WAF rules, rate limiting, bot filtering, IP allow/block lists, OWASP rulesets, Attack Challenge Mode, or any security configuration on the Vercel platform.
vercel-cli
Vercel CLI expert guidance. Use when deploying, managing environment variables, linking projects, viewing logs, managing domains, or interacting with the Vercel platform from the command line.
vercel-api
Vercel MCP and REST API expert guidance. Use when the agent needs live access to Vercel projects, deployments, environment variables, domains, logs, or documentation through the MCP server or REST API.
vercel-agent
Vercel Agent guidance — AI-powered code review, incident investigation, and SDK installation. Automates PR analysis and anomaly debugging. Use when configuring or understanding Vercel's AI development tools.