Agent Skillsvudovn/ag-kit › code-review-checklist

code-review-checklist

GitHub

提供代码审查清单,涵盖正确性、安全、性能、质量及测试等维度。特别针对AI应用,包含提示工程审查和防注入指南,并定义评论分级标准,辅助高效完成代码评审工作。

.agents/skills/code-review-checklist/SKILL.md vudovn/ag-kit

Trigger Scenarios

需要检查代码质量或安全漏洞 进行AI相关代码的提示工程审查

Install

npx skills add vudovn/ag-kit --skill code-review-checklist -g -y
More Options

Non-standard path

npx skills add https://github.com/vudovn/ag-kit/tree/main/.agents/skills/code-review-checklist -g -y

Use without installing

npx skills use vudovn/ag-kit@code-review-checklist

指定 Agent (Claude Code)

npx skills add vudovn/ag-kit --skill code-review-checklist -a claude-code -g -y

安装 repo 全部 skill

npx skills add vudovn/ag-kit --all -g -y

预览 repo 内 skill

npx skills add vudovn/ag-kit --list

SKILL.md

Frontmatter
{
    "name": "code-review-checklist",
    "version": "1.0.0",
    "description": "Code review guidelines covering code quality, security, and best practices.",
    "when_to_use": "When reviewing code for quality, security, and best practices. When the user says 'review my code' or 'check this PR'.",
    "allowed-tools": "Read, Glob, Grep"
}

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 = ...

Review Comments Guide

// Blocking issues use 🔴
🔴 BLOCKING: SQL injection vulnerability here

// Important suggestions use 🟡
🟡 SUGGESTION: Consider using useMemo for performance

// Minor nits use 🟢
🟢 NIT: Prefer const over let for immutable variable

// Questions use ❓
❓ QUESTION: What happens if user is null here?

Version History

  • 211561c Current 2026-08-20 11:38

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Metadata

Files
0
Version
211561c
Hash
07b20413
Indexed
2026-08-20 11:38

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