code-review-checklist

A checklist for reviewing source code for correctness, security, performance, maintainability, testing, documentation, and safe use of AI-generated code.

In plain words
What is it for?
Use it during pull-request reviews to check edge cases, input validation, secret handling, database queries, code structure, tests, comments, and README updates.
Why use it?
It provides a consistent way to catch bugs, security weaknesses, missing tests, slow operations, unclear code, and unsafe assumptions before changes are accepted.

Skill for Claude CodeCodex

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 skills/diillson/chatcli/code-review-checklist
Any agent
npx skills add diillson/chatcli --skill code-review-checklist
Clone the repo
git clone --depth 1 https://github.com/diillson/chatcli

Made for: Claude Code, Codex.

Per session 18 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 642 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 89% 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.

ModelPer sessionOnce invoked
Fable 5 $0.00018 $0.00642
Opus 5 $0.00009 $0.00321
Sonnet 5 $0.00004 $0.00128
Haiku 4.5 $0.00002 $0.00064

Measured 2d ago against content hash 905ec9820ad5, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, 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 2d 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

This is a copy

89% identical to code-review-checklist — 4 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.

.agent/skills/code-review-checklist/SKILL.md · 110 lines

How it starts

The opening of the file, as written. The whole thing — 110 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 (2025)

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 · 110 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. 2d ago First seen · 110 lines · 18 tokens per session scan A 905ec9820ad5

Subscribe to this mod's changes

code-review-checklist is a skill published in the GitHub repository diillson/chatcli (89 stars, last pushed 3d ago), licensed Apache-2.0. It adds 18 tokens to every session and 642 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 89% identical to code-review-checklist, differing in 4 lines, and is treated as a copy.