ag-kit: Skill for Claude Code

.agents/skills/code-review-checklist/SKILL.md

code-review-checklist is a skill for Claude Code from vudovn/ag-kit. It costs 18 tokens per session (681 once invoked), scanned A, original, MIT.

A checklist for reviewing code for correctness, security, performance, maintainability, testing, and documentation.

In plain words
What is it for?
It helps inspect edge cases, injection and cross-site risks, duplicate code, database query patterns, public interfaces, tests, and AI-specific output risks.
Why use it?
It provides a repeatable way to catch bugs, unsafe input handling, exposed secrets, inefficient code, missing tests, and unclear documentation.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: installed under .agents/ (shared by several agents).

This is vudovn/ag-kit's own configuration. It tells Claude Code how to work on ag-kit itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything ag-kit configures →

About the project

AG Kit is a toolkit that gives Google Antigravity coding agents a structured workspace with rules, skills, specialist agents, workflows, persistent memory, orchestration, MCP guidance, and a safety hook. It is for building and operating agent workflows in Antigravity, and its catalogue entries provide parts of that workspace contract.

vudovn/ag-kit · 8,199 stars · on GitHub · ag-kit.unikorn.vn

Reuse

Borrowing it

Nothing to install: this file belongs to vudovn/ag-kit. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/vudovn/ag-kit/main/.agents/skills/code-review-checklist/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/vudovn/ag-kit

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.

agentmods badge for code-review-checklist

README.md
[![agentmods](https://agentmods.dev/badge/skills/vudovn/ag-kit/code-review-checklist/github.svg)](https://agentmods.dev/skills/vudovn/ag-kit/code-review-checklist)
Your own site
<a href="https://agentmods.dev/skills/vudovn/ag-kit/code-review-checklist"><img src="https://agentmods.dev/badge/skills/vudovn/ag-kit/code-review-checklist/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for code-review-checklist

Your own site · 80×15
<a href="https://agentmods.dev/skills/vudovn/ag-kit/code-review-checklist"><img src="https://agentmods.dev/badge/skills/vudovn/ag-kit/code-review-checklist.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 18 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 681 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00018 $0.00681
Opus 5.5 $0.00007 $0.00272
Sonnet 5.5 $0.00004 $0.00136
Haiku 4.5 $0.00002 $0.00068

Measured 1mo ago against content hash 07b20413aa0d, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

code-review-checklist 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 1mo 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.

Origin

Copies of this mod

7 near-identical copies found in the catalogue:

.agents/skills/code-review-checklist/SKILL.md · 112 lines

How it starts

The opening of the file, as written. The whole thing — 112 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Code Review Checklist

Quick Review Checklist

Correctness

  • Code does what it's supposed to do
  • Edge cases handled
  • Error handling in place
  • No obvious bugs

Security

  • Input validated and sanitized
  • No SQL/NoSQL injection vulnerabilities
  • No XSS or CSRF vulnerabilities
  • No hardcoded secrets or sensitive credentials
  • AI-Specific: Protection against Prompt Injection (if applicable)
  • AI-Specific: Outputs are sanitized before being used in critical sinks

Performance

  • No N+1 queries
  • No unnecessary loops
  • Appropriate caching
  • Bundle size impact considered

Code Quality

  • Clear naming
  • DRY - no duplicate code
  • SOLID principles followed
  • Appropriate abstraction level

Testing

  • Unit tests for new code
  • Edge cases tested
  • Tests readable and maintainable

Documentation

  • Complex logic commented
  • Public APIs documented
  • README updated if needed

AI & LLM Review Patterns

Logic & Hallucinations

  • Chain of Thought: Does the logic follow a verifiable path?
  • Edge Cases: Did the AI account for empty states, timeouts, and partial failures?
  • External State: Is the code making safe assumptions about file systems or networks?

Prompt Engineering Review

// ❌ Vague prompt in code
const response = await ai.generate(userInput);

// ✅ Structured & Safe prompt
const response = await ai.generate({
  system: "You are a specialized parser...",
  input: sanitize(userInput),
  schema: ResponseSchema
});

Anti-Patterns to Flag

// ❌ Magic numbers
if (status === 3) { ... }

// ✅ Named constants
if (status === Status.ACTIVE) { ... }

// ❌ Deep nesting
if (a) { if (b) { if (c) { ... } } }

// ✅ Early returns
if (!a) return;
if (!b) return;
if (!c) return;
// do work

// ❌ Long functions (100+ lines)
// ✅ Small, focused functions

// ❌ any type
const data: any = ...

// ✅ Proper types
const data: UserData = ...

Read the full file on GitHub · 112 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. 1mo ago First seen · 112 lines · 18 tokens per session scan A 07b20413aa0d

Subscribe to this mod's changes

code-review-checklist is a skill published in the GitHub repository vudovn/ag-kit (8,199 stars, last pushed 3d ago), licensed MIT. It adds 18 tokens to every session and 681 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-08-30.

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