mcpField
A
agent-reviews

agent-reviews

github.com/pbakausTesting & quality30835 installsUpdated 2w ago
Repository

About agent-reviews

A skill for handling review-bot findings on the current pull request. It separates verified bugs from false positives or uncertain cases, then guides fixes, replies, and follow-up monitoring.

Key features

  1. 01Fetch unanswered bot findings
  2. 02Classify true positives and false positives
  3. 03Ask the user about uncertain findings
  4. 04Commit and reply to processed findings
  5. 05Watch for new bot comments

Use cases

  1. 01Fix verified bugs reported by review bots
  2. 02Document why a bot finding is not applicable
  3. 03Defer uncertain or architectural decisions to the user

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/pbakaus/agent-reviews --skill agent-reviews

After installing, type/agent-reviewsin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

scripts/
agent-reviews.js
comments.js
format.js
github.js

Details

From the project README

Automatically review, fix, and respond to findings from PR review bots on the current PR. Uses a deterministic two-phase workflow: first fix all existing issues, then poll once for new ones.

Path note: All scripts/agent-reviews.js references below are relative to this skill's directory (next to this SKILL.md file). Run them with node.

Phase 1: FETCH & FIX (synchronous)

Step 1: Identify Current PR
gh pr view --json number,url,headRefName

If no PR exists, notify the user and exit.

Step 2: Fetch All Bot Comments (Expanded)

Run scripts/agent-reviews.js --bots-only --unanswered --expanded

This shows only unanswered bot comments with full detail: complete comment body (no truncation), diff hunk (code context), and all replies. Each comment shows its ID in brackets (e.g., [12345678]).

If zero comments are returned, print "No unanswered bot comments found" and skip to Phase 2.

Step 3: Process Each Unanswered Comment

For each comment from the expanded output:

A. Evaluate the Finding

Read the referenced code and determine:

  1. TRUE POSITIVE - A real bug that needs fixing
  2. FALSE POSITIVE - Not actually a bug (intentional behavior, bot misunderstanding)
  3. UNCERTAIN - Not sure; ask the user

Likely TRUE POSITIVE:

  • Code obviously violates stated behavior
  • Missing null checks on potentially undefined values
  • Type mismatches or incorrect function signatures
  • Logic errors in conditionals
  • Missing error handling for documented failure cases

Likely FALSE POSITIVE:

  • Bot doesn't understand the framework/library patterns
  • Code is intentionally structured that way (with comments explaining why)
  • Bot is flagging style preferences, not bugs
  • The "bug" is actually a feature or intentional behavior
  • Bot misread the code flow

When UNCERTAIN — use AskUserQuestion:

  • The fix would require architectural changes
  • You're genuinely unsure if the behavior is intentional
  • The "bug" relates to business logic you don't fully understand
  • Multiple valid interpretations exist
  • The fix could have unintended side effects
B. Act on Evaluation

If TRUE POSITIVE: Fix the code. Track the comment ID and a brief description of the fix.

If FALSE POSITIVE: Do NOT change the code. Track the comment ID and the reason it's not a real bug.

If UNCERTAIN: Use AskUserQuestion. If the user says skip, track it as skipped.

Do NOT reply to comments yet. Replies happen after the commit (Step 5).

Step 4: Commit and Push

After evaluating and fixing ALL unanswered comments:

  1. Run your project's lint and type-check
  2. Stage, commit, and push:
    git add -A
    git commit -m "fix: address PR review bot findings
    
    {List of bugs fixed, grouped by bot}"
    git push
    
  3. Capture the commit hash from the output.
Step 5: Reply to All Comments

Now that the commit hash exists, reply to every processed comment:

For each TRUE POSITIVE:

Run scripts/agent-reviews.js --reply <comment_id> "Fixed in {hash}. {Brief description of the fix}"

For each FALSE POSITIVE:

Run scripts/agent-reviews.js --reply <comment_id> "Won't fix: {reason}. {Explanation of why this is intentional or not applicable}"

For each SKIPPED:

Run scripts/agent-reviews.js --reply <comment_id> "Skipped per user request"

DO NOT start Phase 2 until all replies are posted.


Phase 2: POLL FOR NEW COMMENTS (loop until quiet)

The watcher exits immediately when new comments are found (after a 5s grace period to catch batch posts). This means you run it in a loop: start watcher, process any comments it returns, restart watcher, repeat until the watcher times out with no new comments.

Step 6: Start Watcher Loop

Repeat the following until the watcher exits with no new comments:

6a. Launch the watcher in the background:

Run scripts/agent-reviews.js --watch --bots-only as a background task.

6b. Use TaskOutput to wait for the watcher to complete (blocks up to 12 minutes).

6c. Check the output:

  • If new comments were found (output contains EXITING WITH NEW COMMENTS):

    1. Use --detail <id> to read each new comment's full detail
    2. Process them exactly as in Phase 1, Steps 3-5 (evaluate, fix, commit, push, reply)
    3. Go back to Step 6a to restart the watcher
  • If no new comments (output contains WATCH COMPLETE): Stop looping and move to the Summary Report.


Summary Report

After both phases complete, provide a summary:

## PR Review Bot Resolution Summary

### Results
- Fixed: X bugs
- Already fixed: X bugs
- Won't fix (false positives): X
- Skipped per user: X

### By Bot
#### cursor[bot]
- BUG-001: {description} - Fixed in {commit}
- BUG-002: {description} - Won't fix: {reason}

#### Copilot
- {description} - Fixed in {commit}

### Status
✅ All findings addressed. Watch completed.

Important Notes

Response Policy
  • Every finding gets a response - No silent ignores
  • Responses help train bots and document decisions
  • "Won't fix" responses prevent the same false positive from being re-raised
User Interaction
  • Use AskUserQuestion when uncertain about a finding
  • Don't guess on architectural or business logic questions
  • It's better to ask than to make a wrong fix or wrong dismissal
Best Practices
  • Verify findings before fixing - bots have false positives
  • Keep fixes minimal and focused - don't refactor unrelated code
  • Ensure type-check and lint pass before committing
  • Group related fixes into a single commit
  • Copilot suggestion blocks often contain ready-to-use fixes

Comments

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