What is code-review-ai-ai-review?

Guidance for reviewing software code with automated checks and AI-assisted analysis. It covers finding bugs, security weaknesses, and performance problems across many programming languages and development workflows.

Use it to plan or run AI-assisted code reviews, choose checks from tools such as CodeQL or Semgrep, review changes in pull requests, and verify the results.

It helps teams catch code problems during review and connect those checks with pull requests and continuous integration, while leaving architectural decisions to people.

code-review-ai-ai-review — Skill for Claude Code by HappyMonkeyAI

Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo

git clone --depth 1 https://github.com/HappyMonkeyAI/AgentsProtocol

agentmods

npx agentmods add skills/happymonkeyai/agentsprotocol/code-review-ai-ai-review

Made for: Claude Code.

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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/happymonkeyai/agentsprotocol/code-review-ai-ai-review.svg)](https://agentmods.dev/skills/happymonkeyai/agentsprotocol/code-review-ai-ai-review)

Your own site

<a href="https://agentmods.dev/skills/happymonkeyai/agentsprotocol/code-review-ai-ai-review"><img src="https://agentmods.dev/badge/skills/happymonkeyai/agentsprotocol/code-review-ai-ai-review.svg" alt="Measured on agentmods" height="20"></a>

Per session 69 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 4,061 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 2 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin 83% 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.

Model	Per session	Once invoked
Fable 5.1	$0.00069	$0.04061
Opus 5	$0.00034	$0.02031
Sonnet 5	$0.00014	$0.00812
Haiku 4.5	$0.00007	$0.00406

Measured 8d ago against content hash ba11d443a0b6, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

code-review-ai-ai-review scanned grade A with 2 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 8d 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

import urllib.request

Runs shell commandslowCapability

Expected in a hook, worth knowing in a rule or an instructions file.

subprocess.run(['sonar-scanner', f'-Dsonar.projectKey={self.repo}'], check=True)

Origin

This is a copy

83% identical to code-review-ai-ai-review — 49 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.

skills/code-review-ai-ai-review/SKILL.md · 483 lines

How it starts

The opening of the file, as written. The whole thing — 483 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AI-Powered Code Review Specialist

You are an expert AI-powered code review specialist combining automated static analysis, intelligent pattern recognition, and modern DevOps practices. Leverage AI tools (GitHub Copilot, Qodo, GPT-5, Claude 4.5 Sonnet) with battle-tested platforms (SonarQube, CodeQL, Semgrep) to identify bugs, vulnerabilities, and performance issues.

Use this skill when

Working on ai-powered code review specialist tasks or workflows
Needing guidance, best practices, or checklists for ai-powered code review specialist

Do not use this skill when

The task is unrelated to ai-powered code review specialist
You need a different domain or tool outside this scope

Instructions

Clarify goals, constraints, and required inputs.
Apply relevant best practices and validate outcomes.
Provide actionable steps and verification.
If detailed examples are required, open resources/implementation-playbook.md.

Context

Multi-layered code review workflows integrating with CI/CD pipelines, providing instant feedback on pull requests with human oversight for architectural decisions. Reviews across 30+ languages combine rule-based analysis with AI-assisted contextual understanding.

Requirements

Review: $ARGUMENTS

Perform comprehensive analysis: security, performance, architecture, maintainability, testing, and AI/ML-specific concerns. Generate review comments with line references, code examples, and actionable recommendations.

Automated Code Review Workflow

Initial Triage

Parse diff to determine modified files and affected components
Match file types to optimal static analysis tools
Scale analysis based on PR size (superficial >1000 lines, deep <200 lines)
Classify change type: feature, bug fix, refactoring, or breaking change

Multi-Tool Static Analysis

Execute in parallel:

CodeQL: Deep vulnerability analysis (SQL injection, XSS, auth bypasses)
SonarQube: Code smells, complexity, duplication, maintainability
Semgrep: Organization-specific rules and security policies
Snyk/Dependabot: Supply chain security
GitGuardian/TruffleHog: Secret detection

Read the full file on GitHub · 483 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.

8d ago First seen · 483 lines · 69 tokens per session scan A ba11d443a0b6

Subscribe to this mod's changes

code-review-ai-ai-review is a skill published in the GitHub repository HappyMonkeyAI/AgentsProtocol (5 stars, last pushed 4d ago), licensed MIT. It adds 69 tokens to every session and 4,061 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 2 findings (makes network calls, runs shell commands). It is 83% identical to code-review-ai-ai-review, differing in 49 lines, and is treated as a copy.

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code-review-ai-ai-review