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Pr Review Response

CommunityPopular
bradygaster
pr-review-response

Teaches agents to reply to PR review comment threads after fixing issues, making resolutions traceable

Overview

Publisherbradygaster
Repositorysquad
Skill namepr-review-response
Stars
3.3K
Forks
506
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by bradygaster on GitHub. Read the source before you install it.

Installation

Install the Pr Review Response AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/bradygaster/squad/tree/dev/packages/squad-cli/templates/skills/pr-review-response
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/bradygaster/squad.git /tmp/squad
mkdir -p .claude/skills
cp -r /tmp/squad/packages/squad-cli/templates/skills/pr-review-response .claude/skills/pr-review-response
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Pr Review Response in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Pr Review Response on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Pr Review Response is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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):

bash
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)

Step 3: Reply to each review thread

After fixing and committing, reply to each review comment thread individually.

REST API call (via gh CLI):

bash
gh api repos/{owner}/{repo}/pulls/{pr_number}/comments/{comment_id}/replies \
  -f body="Fixed in {sha_short} — {brief description of what was changed}"

Important: {comment_id} must be the ID of the top-level comment in the thread. You cannot reply to a reply — only to the original review comment.

Example replies:

bash
# Specific and traceable
gh api repos/bradygaster/squad/pulls/42/comments/18234/replies \
  -f body="Fixed in a1b2c3d — switched to path.dirname(squadDirInfo.path) for worktree consistency"

# When applying a suggested code change
gh api repos/bradygaster/squad/pulls/42/comments/18235/replies \
  -f body="Applied suggestion — updated error message to include the file path for debuggability"

# When pushing back on a suggestion
gh api repos/bradygaster/squad/pulls/42/comments/18236/replies \
  -f body="Considered but not applied — this path needs to stay absolute because worktree resolution depends on it. See detectSquadDir() in detect-squad-dir.ts."

Step 4: Resolve threads (optional, GraphQL only)

Thread resolution is only available via the GitHub GraphQL API. Use this when your fix fully addresses the comment and no further discussion is needed.

First, get the thread IDs (they're different from comment IDs):

bash
gh api graphql -f query='
  query {
    repository(owner: "{owner}", name: "{repo}") {
      pullRequest(number: {pr_number}) {
        reviewThreads(first: 100) {
          nodes {
            id
            isResolved
            comments(first: 1) {
              nodes { body databaseId }
            }
          }
        }
      }
    }
  }
'

Match thread IDs to comment IDs using databaseId, then resolve:

bash
gh api graphql -f query='
  mutation {
    resolveReviewThread(input: {threadId: "{thread_node_id}"}) {
      thread { id isResolved }
    }
  }
'

When to resolve vs. leave open:

  • ✅ Resolve: You fixed exactly what was requested, no ambiguity
  • ❌ Don't resolve: You pushed back, applied a different fix, or the comment needs further discussion
  • ❌ Don't resolve: The reviewer is a human — let them confirm and resolve themselves

Rule of thumb: Agent-to-agent threads (e.g., Copilot review → agent fix) can be resolved by the fixer. Human reviewer threads should be left for the human to resolve.

Step 5: Commit message traceability

Commit messages should reference the PR context:

fix: address review feedback on PR #{pr_number}

- Switched to path.dirname() for worktree path resolution (comment #18234)
- Updated error message to include file path (comment #18235)

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

For single-comment fixes, a shorter format works:

fix: use path.dirname() for worktree consistency (PR #{pr_number} review)

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

AGENT WORKFLOW (Summary)

  1. READ — Fetch review threads using MCP tool or gh api
  2. FIX — Make code changes, tracking comment ID → change mapping
  3. COMMIT — Push with traceable commit message referencing PR and comments
  4. REPLY — Post individual reply to each thread via gh api .../replies
  5. RESOLVE — (Optional) Resolve agent-to-agent threads via GraphQL
  6. STOP — Do not batch-reply, do not skip threads, do not resolve human threads

Examples

Example: Copilot flags a potential null dereference

Review comment (id: 55123):

squadDir could be undefined here. Consider adding a null check.

Agent workflow:

  1. Read the comment via get_review_comments
  2. Add the null check in src/cli/core/detect-squad-dir.ts
  3. Commit: fix: add null check for squadDir (PR #99 review)
  4. Reply:
    bash
    gh api repos/bradygaster/squad/pulls/99/comments/55123/replies \
      -f body="Fixed in f4e5d6c — added early return when squadDir is undefined, matching the pattern in loadConfig()"
  5. Resolve the thread (Copilot → agent, safe to resolve)

Example: Multiple review comments on one PR

Comments:

  • id: 55123 — "Null check needed" on detect-squad-dir.ts:42
  • id: 55124 — "Consider using path.join()" on detect-squad-dir.ts:58
  • id: 55125 — "This log message is too verbose" on output.ts:15

Agent handles each individually:

bash
# Fix all three, commit
git add packages/squad-cli/src/cli/core/detect-squad-dir.ts packages/squad-cli/src/cli/core/output.ts
git commit -m "fix: address 3 review comments on PR #99

- Added null check for squadDir (comment #55123)
- Switched to path.join() for cross-platform paths (comment #55124)
- Reduced log verbosity to debug level (comment #55125)"

git push

# Reply to each thread individually
gh api repos/bradygaster/squad/pulls/99/comments/55123/replies \
  -f body="Fixed — added early return when squadDir is undefined"

gh api repos/bradygaster/squad/pulls/99/comments/55124/replies \
  -f body="Fixed — switched to path.join(squadDir, 'config.json') for cross-platform consistency"

gh api repos/bradygaster/squad/pulls/99/comments/55125/replies \
  -f body="Fixed — changed from console.log to debug() so it only shows with --verbose flag"

Example: Handling Copilot suggestion blocks

Copilot sometimes provides suggestion blocks with exact code to apply:

Review comment (id: 55130):

Consider using optional chaining:
```suggestion
const name = config?.agent?.name ?? 'default';
```

Reply format when applying:

bash
gh api repos/bradygaster/squad/pulls/99/comments/55130/replies \
  -f body="Applied suggestion — using optional chaining with nullish coalescing"

Reply format when not applying:

bash
gh api repos/bradygaster/squad/pulls/99/comments/55130/replies \
  -f body="Not applied — config is guaranteed non-null at this point (validated on line 12). Optional chaining would mask errors."

Example: Pushing back on a review comment

Not every review comment should be accepted. When a suggestion is incorrect or doesn't apply:

bash
gh api repos/bradygaster/squad/pulls/99/comments/55140/replies \
  -f body="Considered but not applied — this file is in the zero-dependency bootstrap set (see copilot-instructions.md § Protected Files). Adding path.join() would require importing from the SDK, which breaks the bootstrap constraint."

Do NOT resolve the thread when pushing back. Leave it open for the reviewer to confirm.

Anti-Patterns

  • ❌ Fixing silently — Making code changes without replying to the review thread. The reviewer has no way to know which comments were addressed.
  • ❌ Batch-replying "all fixed" — A single comment saying "Addressed all review feedback" on the PR. Each thread needs its own reply so reviewers can verify individually.
  • ❌ Resolving without explaining — Marking threads resolved without posting a reply first. The resolution gives no context on what was done.
  • ❌ Resolving human reviewer threads — Only resolve threads from automated reviewers (Copilot, bots). Let human reviewers confirm and resolve their own threads.
  • ❌ Vague replies — "Fixed" or "Done" without saying what was changed. The reply should be specific enough that the reviewer doesn't need to re-read the diff.
  • ❌ Replying before pushing — Reply after your fix is committed and pushed, not before. The reply should reference actual committed code.
  • ❌ Ignoring comments you disagree with — If you don't apply a suggestion, reply explaining why. Silence looks like you missed it.
  • ❌ Replying to replies — The REST API only supports replying to top-level review comments. Attempting to reply to a reply will fail with a 404.

Frequently asked questions

What does the Pr Review Response AI skill do?

Teaches agents to reply to PR review comment threads after fixing issues, making resolutions traceable

Why use Pr Review Response on TypingMind?

Because you install it once and use it with any model. Pr Review Response is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Pr Review Response in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/bradygaster/squad/tree/dev/packages/squad-cli/templates/skills/pr-review-response. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Pr Review Response?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Pr Review Response?

As many as you like. As long as a model supports skills, you can use Pr Review Response with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Pr Review Response AI skill free?

Yes. It is published on GitHub by bradygaster under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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