GitHub Agentic Workflows is a GitHub CLI extension that lets developers define AI-assisted repository automation in Markdown and run it through GitHub Actions. It is intended for tasks requiring interpretation or reasoning, such as issue triage, pull-request review, CI investigation, documentation maintenance, and dependency analysis. The catalogue entries provide skills and agents for working with these workflows.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add github/gh-aw --skill pr-review-responsegit clone --depth 1 https://github.com/github/gh-awWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/github/gh-aw/pr-review-response)<a href="https://agentmods.dev/skills/github/gh-aw/pr-review-response"><img src="https://agentmods.dev/badge/skills/github/gh-aw/pr-review-response/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/github/gh-aw/pr-review-response"><img src="https://agentmods.dev/badge/skills/github/gh-aw/pr-review-response.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00022 | $0.02574 |
| Opus 5.5 | $0.00009 | $0.01030 |
| Sonnet 5.5 | $0.00004 | $0.00515 |
| Haiku 4.5 | $0.00002 | $0.00257 |
Grade A, and why
pr-review-response scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
3 near-identical copies found in the catalogue:
- pr-review-response — 100% identical, 0 lines differ
- pr-review-response — 100% identical, 0 lines differ
- pr-review-response — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 269 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Context
When an agent fixes code in response to PR review comments (from Copilot, a human reviewer, or any GitHub reviewer), the fix alone is not enough. The reviewer needs to see — on the PR thread itself — which comments were addressed and how. Without replies, comments stay visually unresolved, reviewers must re-read the entire diff to verify fixes, and there's no traceable link between feedback and resolution.
Use this skill whenever:
- You are fixing code based on PR review feedback
- You are addressing Copilot review suggestions
- You are responding to reviewer-requested changes on a PR
- A squad member hands you review comments to resolve
SCOPE
✅ THIS SKILL PRODUCES:
- Reply comments on each review thread explaining the fix
- Optionally resolved threads (via GraphQL when appropriate)
- Commit messages that reference the PR and review context
❌ THIS SKILL DOES NOT PRODUCE:
- The code fixes themselves (that's the agent's domain work)
- New review comments or reviews
- PR descriptions or summaries
Patterns
Step 1: Read the review comments
Using MCP tools (preferred when available):
github-mcp-server-pull_request_read
method: "get_review_comments"
owner: "{owner}"
repo: "{repo}"
pullNumber: {pr_number}
This returns review threads with metadata: isResolved, isOutdated, isCollapsed, and their associated comments. Each comment has an id you'll need for replies.
Using gh CLI (fallback):
gh api repos/{owner}/{repo}/pulls/{pr_number}/comments --paginate
Each comment object contains id, body, path, line, and in_reply_to_id. Top-level comments have no in_reply_to_id — those are the ones you reply to.
Step 2: Fix the code
Make the actual code changes. This is your normal domain work — the skill doesn't prescribe how to fix, only how to communicate the fix.
Track what you changed. For each review comment, note:
- The comment
id(top-level, not a reply) - The file and line referenced
- What you actually changed (brief description)
- The commit SHA after pushing (if available)
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2mo ago First seen · 269 lines · 22 tokens per session scan A fe66f6493cc1
pr-review-response is a skill published in the GitHub repository github/gh-aw (5,579 stars, last pushed yesterday), licensed MIT. It adds 22 tokens to every session and 2,574 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
pr-review-response compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| pr-review-responsegithub/gh-aw | Skill | 5.6k | yesterday | MIT | A | 22 | Claude Code, Codex |
| watch-prjustincampbell/gh-watch | Skill | 4 | 7d ago | MIT | A | 48 | Claude Code |
| ci-cdLuuOW/meridian-mcp | Skill | 0 | 24d ago | MIT | C | 48 | Claude Code, Codex |
| deployjeremylongshore/tons-of-skills-marketplace | Skill | 2.9k | yesterday | MIT | A | 76 | Claude Code |
| code-review-githubinitializ/forge | Skill | 235 | yesterday | Apache-2.0 | A | 30 | Claude Code, Codex |
| release-habit-hookshabit-hooks/habit-hooks | Skill | 250 | 1mo ago | MIT | A | 56 | Claude Code, Codex |
| habit-hooks-reviewhabit-hooks/habit-hooks | Skill | 250 | 1mo ago | MIT | A | 51 | Claude Code, Codex |