pr-review-response

pr-review-response is a skill for Claude Code, Codex from DanWahlin/ai-agent-board. It costs 22 tokens per session (2,574 once invoked), scanned A, a copy of pr-review-response, MIT.

A guide for replying to code-review discussions on a pull request, which is a proposed change shared for review. It helps an agent explain on each review thread how the requested fix was handled.

In plain words
What is it for?
Use it after fixing issues raised by a human, Copilot, or another GitHub reviewer. It helps write replies, optionally close resolved threads, and reference the review context in commits.
Why use it?
A code change alone may leave reviewers unsure which feedback was addressed. Replies create a clear connection between each comment and the corresponding fix.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it after fixing issues raised by a human, Copilot, or another GitHub reviewer. It helps write replies, optionally close resolved threads, and reference the review context in commits.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/danwahlin/ai-agent-board/pr-review-response
Install

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.

Any agent
npx skills add DanWahlin/ai-agent-board --skill pr-review-response
Clone the repo
git clone --depth 1 https://github.com/DanWahlin/ai-agent-board

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for pr-review-response

README.md
[![agentmods](https://agentmods.dev/badge/skills/danwahlin/ai-agent-board/pr-review-response/github.svg)](https://agentmods.dev/skills/danwahlin/ai-agent-board/pr-review-response)
Your own site
<a href="https://agentmods.dev/skills/danwahlin/ai-agent-board/pr-review-response"><img src="https://agentmods.dev/badge/skills/danwahlin/ai-agent-board/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.

agentmods 80×15 button for pr-review-response

Your own site · 80×15
<a href="https://agentmods.dev/skills/danwahlin/ai-agent-board/pr-review-response"><img src="https://agentmods.dev/badge/skills/danwahlin/ai-agent-board/pr-review-response.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 22 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,574 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 100% copy Near-identical to another mod in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00022 $0.02574
Opus 5 $0.00011 $0.01287
Sonnet 5 $0.00004 $0.00515
Haiku 4.5 $0.00002 $0.00257

Measured 11d ago against content hash fe66f6493cc1, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

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 11d 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.

Origin

This is a copy

100% identical to pr-review-response — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.squad/templates/skills/pr-review-response/SKILL.md · 269 lines

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)

Read the full file on GitHub · 269 lines

Changes

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.

  1. 11d ago First seen · 269 lines · 22 tokens per session scan A fe66f6493cc1

Subscribe to this mod's changes

pr-review-response is a skill published in the GitHub repository DanWahlin/ai-agent-board (58 stars, last pushed 16d ago), licensed MIT. It adds 22 tokens to every session and 2,574 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to pr-review-response, differing in 0 lines, and is treated as a copy.

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