code-review

name	code-review
description	Automated code review for pull requests using multiple specialized agents with confidence-based scoring
source	Claude Plugin Conversion
license	Converted from Claude plugin - check original LICENSE

code-review

Automated code review for pull requests using multiple specialized agents with confidence-based scoring

Overview

This skill was converted from a Claude plugin. Original plugin structure:

code-review.md README.md 

Original README

# Code Review Plugin

Automated code review for pull requests using multiple specialized agents with confidence-based scoring to filter false positives.

## Overview

The Code Review Plugin automates pull request review by launching multiple agents in parallel to independently audit changes from different perspectives. It uses confidence scoring to filter out false positives, ensuring only high-quality, actionable feedback is posted.

## Commands

### `/code-review`

Performs automated code review on a pull request using multiple specialized agents.

**What it does:**
1. Checks if review is needed (skips closed, draft, trivial, or already-reviewed PRs)
2. Gathers relevant CLAUDE.md guideline files from the repository
3. Summarizes the pull request changes
4. Launches 4 parallel agents to independently review:
   - **Agents #1 & #2**: Audit for CLAUDE.md compliance
   - **Agent #3**: Scan for obvious bugs in changes
   - **Agent #4**: Analyze git blame/history for context-based issues
5. Scores each issue 0-100 for confidence level
6. Filters out issues below 80 confidence threshold
7. Posts review comment with high-confidence issues only

**Usage:**
```bash
/code-review
```

**Example workflow:**
```bash
# On a PR branch, run:
/code-review

# Claude will:
# - Launch 4 review agents in parallel
# - Score each issue for confidence
# - Post comment with issues ≥80 confidence
# - Skip posting if no high-confidence issues found
```

**Features:**
- Multiple independent agents for comprehensive review
- Confidence-based scoring reduces false positives (threshold: 80)
- CLAUDE.md compliance checking with explicit guideline verification
- Bug detection focused on changes (not pre-existing issues)
- Historical context analysis via git blame
- Automatic skipping of closed, draft, or already-reviewed PRs

Commands

The original plugin provided these commands:

Code Review

# Original command: /code-review

---
allowed-tools: Bash(gh issue view:*), Bash(gh search:*), Bash(gh issue list:*), Bash(gh pr comment:*), Bash(gh pr diff:*), Bash(gh pr view:*), Bash(gh pr list:*)
description: Code review a pull request
disable-model-invocation: false
---

Provide a code review for the given pull request.

To do this, follow these steps precisely:

1. Use a Haiku agent to check if the pull request (a) is closed, (b) is a draft, (c) does not need a code review (eg. because it is an automated pull request, or is very simple and obviously ok), or (d) already has a code review from you from earlier. If so, do not proceed.
2. Use another Haiku agent to give you a list of file paths to (but not the contents of) any relevant CLAUDE.md files from the codebase: the root CLAUDE.md file (if one exists), as well as any CLAUDE.md files in the directories whose files the pull request modified
3. Use a Haiku agent to view the pull request, and ask the agent to return a summary of the change
4. Then, launch 5 parallel Sonnet agents to independently code review the change. The agents should do the following, then return a list of issues and the reason each issue was flagged (eg. CLAUDE.md adherence, bug, historical git context, etc.):
   a. Agent #1: Audit the changes to make sure they compily with the CLAUDE.md. Note that CLAUDE.md is guidance for Claude as it writes code, so not all instructions will be applicable during code review.
   b. Agent #2: Read the file changes in the pull request, then do a shallow scan for obvious bugs. Avoid reading extra context beyond the changes, focusing just on the changes themselves. Focus on large bugs, and avoid small issues and nitpicks. Ignore likely false positives.
   c. Agent #3: Read the git blame and history of the code modified, to identify any bugs in light of that historical context
   d. Agent #4: Read previous pull requests that touched these files, and check for any comments on those pull requests that may also apply to the current pull request.
   e. Agent #5: Read code comments in the modified files, and make sure the changes in the pull request comply with any guidance in the comments.
5. For each issue found in #4, launch a parallel Haiku agent that takes the PR, issue description, and list of CLAUDE.md files (from step 2), and returns a score to indicate the agent's level of confidence for whether the issue is real or false positive. To do that, the agent should score each issue on a scale from 0-100, indicating its level of confidence. For issues that were flagged due to CLAUDE.md instructions, the agent should double check that the CLAUDE.md actually calls out that issue specifically. The scale is (give this rubric to the agent verbatim):
   a. 0: Not confident at all. This is a false positive that doesn't stand up to light scrutiny, or is a pre-existing issue.
   b. 25: Somewhat confident. This might be a real issue, but may also be a false positive. The agent wasn't able to verify that it's a real issue. If the issue is stylistic, it is one that was not explicitly called out in the relevant CLAUDE.md.
   c. 50: Moderately confident. The agent was able to verify this is a real issue, but it might be a nitpick or not happen very often in practice. Relative to the rest of the PR, it's not very important.
   d. 75: Highly confident. The agent double checked the issue, and verified that it is very likely it is a real issue that will be hit in practice. The existing approach in the PR is insufficient. The issue is very important and will directly impact the code's functionality, or it is an issue that is directly mentioned in the relevant CLAUDE.md.
   e. 100: Absolutely certain. The agent double checked the issue, and confirmed that it is definitely a real issue, that will happen frequently in practice. The evidence directly confirms this.
6. Filter out any issues with a score less than 80. If there are no issues that meet this criteria, do not proceed.
7. Use a Haiku agent to repeat the eligibility check from #1, to make sure that the pull request is still eligible for code review.
8. Finally, use the gh bash command to comment back on the pull request with the result. When writing your comment, keep in mind to:
   a. Keep your output brief
   b. Avoid emojis
   c. Link and cite relevant code, files, and URLs

Examples of false positives, for steps 4 and 5:

- Pre-existing issues
- Something that looks like a bug but is not actually a bug
- Pedantic nitpicks that a senior engineer wouldn't call out
- Issues that a linter, typechecker, or compiler would catch (eg. missing or incorrect imports, type errors, broken tests, formatting issues, pedantic style issues like newlines). No need to run these build steps yourself -- it is safe to assume that they will be run separately as part of CI.
- General code quality issues (eg. lack of test coverage, general security issues, poor documentation), unless explicitly required in CLAUDE.md
- Issues that are called out in CLAUDE.md, but explicitly silenced in the code (eg. due to a lint ignore comment)
- Changes in functionality that are likely intentional or are directly related to the broader change
- Real issues, but on lines that the user did not modify in their pull request

Notes:

- Do not check build signal or attempt to build or typecheck the app. These will run separately, and are not relevant to your code review.
- Use `gh` to interact with Github (eg. to fetch a pull request, or to create inline comments), rather than web fetch
- Make a todo list first
- You must cite and link each bug (eg. if referring to a CLAUDE.md, you must link it)
- For your final comment, follow the following format precisely (assuming for this example that you found 3 issues):

---

### Code review

Found 3 issues:

1. <brief description of bug> (CLAUDE.md says "<...>")

<link to file and line with full sha1 + line range for context, note that you MUST provide the full sha and not use bash here, eg. https://github.com/anthropics/claude-code/blob/1d54823877c4de72b2316a64032a54afc404e619/README.md#L13-L17>

2. <brief description of bug> (some/other/CLAUDE.md says "<...>")

<link to file and line with full sha1 + line range for context>

3. <brief description of bug> (bug due to <file and code snippet>)

<link to file and line with full sha1 + line range for context>

🤖 Generated with [Claude Code](https://claude.ai/code)

<sub>- If this code review was useful, please react with 👍. Otherwise, react with 👎.</sub>

---

- Or, if you found no issues:

---

### Code review

No issues found. Checked for bugs and CLAUDE.md compliance.

🤖 Generated with [Claude Code](https://claude.ai/code)

- When linking to code, follow the following format precisely, otherwise the Markdown preview won't render correctly: https://github.com/anthropics/claude-cli-internal/blob/c21d3c10bc8e898b7ac1a2d745bdc9bc4e423afe/package.json#L10-L15
  - Requires full git sha
  - You must provide the full sha. Commands like `https://github.com/owner/repo/blob/$(git rev-parse HEAD)/foo/bar` will not work, since your comment will be directly rendered in Markdown.
  - Repo name must match the repo you're code reviewing
  - # sign after the file name
  - Line range format is L[start]-L[end]
  - Provide at least 1 line of context before and after, centered on the line you are commenting about (eg. if you are commenting about lines 5-6, you should link to `L4-7`)

Usage as OpenClaw Skill

This skill provides similar functionality to the original Claude plugin. When using this skill:

1. Trigger: Mention "code-review" or related keywords
2. Context: Provide the same input you would give to the original plugin
3. Output: Expect similar results formatted for OpenClaw

Conversion Notes

• This is an automated conversion and may need manual refinement
• Some plugin-specific features may not be fully replicated
• Commands are now triggered by natural language instead of slash commands
• Multi-agent coordination is simulated through sequential reasoning

Original Structure

anthropic-official-plugins/plugins/code-review
├── commands
│   └── code-review.md
├── LICENSE
└── README.md

1 directory, 3 files