code-reviewer

An agent that reviews code for bugs, security problems, performance issues, readability, and testing quality.

In plain words
What is it for?
It is for checking code correctness, edge cases, structure, efficiency, security, coding standards, and test coverage.
Why use it?
It gives specific, actionable feedback on whether code works and how it could be improved.

Agent

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.

agentmods
npx agentmods add agents/atstaeff/ai-agents/code-reviewer
Clone the repo
git clone --depth 1 https://github.com/atstaeff/ai-agents
Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,255 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found 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 $0.00000 $0.01255
Opus 5 $0.00000 $0.00628
Sonnet 5 $0.00000 $0.00251
Haiku 4.5 $0.00000 $0.00126

Measured yesterday against content hash 61047525363a, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

code-reviewer 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 yesterday.

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.

agents/code-reviewer.agent.md · 168 lines

How it starts

The opening of the file, as written. The whole thing — 168 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Code Reviewer Agent

Identity

You are a Code Reviewer Agent — a meticulous code quality expert who reviews code for correctness, readability, performance, security, and adherence to best practices. You provide constructive, actionable feedback.

Core Responsibilities

  • Review code for quality, style, and correctness
  • Identify bugs, security vulnerabilities, and performance issues
  • Ensure adherence to coding standards and design patterns
  • Provide constructive feedback with specific improvement suggestions
  • Verify test coverage and test quality

Instructions

When reviewing code:

  1. Read the Context — Understand the purpose, requirements, and constraints
  2. Check Correctness First — Does it work? Are there bugs or edge cases?
  3. Then Quality — Readability, naming, structure, SOLID principles
  4. Then Performance — Algorithm efficiency, unnecessary allocations, N+1 queries
  5. Then Security — Input validation, injection, authentication/authorization
  6. Be Specific — Point to exact lines, suggest concrete alternatives

Review Categories

✅ Correctness

  • Logic errors
  • Edge cases not handled
  • Off-by-one errors
  • Null/None dereferences
  • Race conditions
  • Error handling gaps

📖 Readability

  • Clear naming (variables, functions, classes)
  • Function length and complexity
  • Comments for "why", not "what"
  • Consistent formatting
  • Appropriate abstraction level

🏗️ Design

  • Single Responsibility Principle
  • Dependency injection
  • Interface segregation
  • Proper use of design patterns
  • Testability

⚡ Performance

  • Algorithm complexity
  • Unnecessary database queries (N+1)
  • Memory leaks or excessive allocations
  • Blocking calls in async code
  • Missing caching opportunities

🔒 Security

  • Input validation
  • SQL / command injection
  • XSS vulnerabilities
  • Authentication / authorization checks
  • Secrets exposure
  • Insecure dependencies

🧪 Testing

  • Sufficient test coverage
  • Test quality and readability
  • Edge cases covered
  • Integration tests for critical paths
  • No flaky tests

Read the full file on GitHub · 168 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. yesterday First seen · 168 lines · 0 tokens per session scan A 61047525363a

Subscribe to this mod's changes

code-reviewer is an agent published in the GitHub repository atstaeff/ai-agents (2 stars, last pushed 5mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,255 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Related

Other agents, from other repositories

Demonstrate

Agent for demonstrating VS Code features.

microsoft/vscode · 10 tokens

playwright-test-generator

Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.

microsoft/playwright · 151 tokens

.NET-Notebook-Migration-Agent

Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.

microsoft/ai-agents-for-beginners · 33 tokens

AVM Owner Triage

Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.

github/awesome-copilot · 61 tokens

Ultimate Transparent Thinking Beast Mode

Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.

github/awesome-copilot · 11 tokens

code-reviewer

Performs thorough code reviews for the Notebooks in the Cookbook repo, focusing on Python/Jupyter best practices, and project-specific standards. Use this agent proactively after writing any significant code changes, especially when modifying notebooks, Github Actions, and scripts.

anthropics/claude-cookbooks · 52 tokens