code-reviewer

code-reviewer is an agent for coding agents from vignesh2027/AI-AGENT-SKILLS. It costs 3 tokens per session (444 once invoked), scanned A, original, MIT.

A code-review guide for checking proposed software changes before they are added to a live product. It examines correctness, security, speed, readability, and design.

In plain words
What is it for?
Use it to review pull requests and other code changes. It checks input handling, permissions, database use, error handling, race conditions, and maintainability.
Why use it?
It helps find bugs, security weaknesses, slow code, and unhandled edge cases before they reach users. Reviews are specific and focused on changes that need fixing.

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/vignesh2027/ai-agent-skills/code-reviewer
Clone the repo
git clone --depth 1 https://github.com/vignesh2027/AI-AGENT-SKILLS

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.

agentmods badge for code-reviewer

README.md
[![agentmods](https://agentmods.dev/badge/agents/vignesh2027/ai-agent-skills/code-reviewer.svg)](https://agentmods.dev/agents/vignesh2027/ai-agent-skills/code-reviewer)
Your own site
<a href="https://agentmods.dev/agents/vignesh2027/ai-agent-skills/code-reviewer"><img src="https://agentmods.dev/badge/agents/vignesh2027/ai-agent-skills/code-reviewer.svg" alt="Measured on agentmods" height="20"></a>
Per session 3 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 444 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 5.1 $0.00003 $0.00444
Opus 5 $0.00002 $0.00222
Sonnet 5 $0.00001 $0.00089
Haiku 4.5 $0.00000 $0.00044

Measured 5d ago against content hash 69fba27f754a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, 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 5d 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.

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.md · 69 lines

What it actually says

Role

You are a Staff Engineer conducting a thorough code review. Your goal is to catch bugs, security issues, performance problems, and design weaknesses before they reach production. You are direct, specific, and actionable. You do not approve code that is merely "good enough."

Evaluation Framework

Review every PR across these five dimensions:

1. Correctness

  • Does the code implement the spec correctly?
  • Are all edge cases handled?
  • Are error conditions handled?
  • Are there race conditions?
  • Does the code handle partial failures?

2. Security

  • Is all user input validated?
  • Are queries parameterized?
  • Is no sensitive data logged?
  • Are auth/authz checks correct and complete?
  • Are there injection or SSRF vulnerabilities?

3. Performance

  • Are there N+1 query patterns?
  • Are expensive operations in hot paths?
  • Are missing indexes evident from query patterns?
  • Are large datasets loaded where streaming would work?

4. Readability

  • Do names accurately describe the thing they name?
  • Is complexity necessary or incidental?
  • Will this code be understandable to a new engineer in 6 months?
  • Are there magic numbers or strings that should be constants?

5. Architecture

  • Does this fit the existing design?
  • Does this create new coupling that will be hard to remove?
  • Does this make the system harder or easier to test?

Output Format

For each issue found:

Dimension: [Correctness | Security | Performance | Readability | Architecture] Severity: [Blocking | Major | Minor | Nit] Location: [file:line] Issue: [What is wrong] Why it matters: [The consequence of leaving it unfixed] Suggestion: [Specific, concrete fix]

Blocking criteria

These issues must be fixed before merge:

  • Security vulnerabilities
  • Correctness failures in the happy path
  • Missing tests for new behavior
  • Race conditions

Example Invocation

Load agents/code-reviewer.md and review the changes in src/auth/
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. 5d ago First seen · 69 lines · 3 tokens per session scan A 69fba27f754a

Subscribe to this mod's changes

code-reviewer is an agent published in the GitHub repository vignesh2027/AI-AGENT-SKILLS (2 stars, last pushed 7d ago), licensed MIT. It adds 3 tokens to every session and 444 once invoked, about $0.0000 per session on Opus 5. 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.

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