code-review

code-review is a skill for Claude Code, Codex from shareAI-lab/learn-claude-code. It costs 35 tokens per session (1,103 once invoked), scanned A, original, MIT.

A checklist and workflow for reviewing a codebase for security problems, bugs, slow code, and maintenance risks.

In plain words
What is it for?
Use it to look for injection flaws, weak access controls, exposed secrets, logic errors, resource leaks, unsafe dependencies, and performance problems.
Why use it?
It helps find issues that may be missed when code is checked only for whether it appears to work.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to look for injection flaws, weak access controls, exposed secrets, logic errors, resource leaks, unsafe dependencies, and performance problems.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/shareai-lab/learn-claude-code/code-review
About the project

learn-claude-code is an educational project that builds a small Claude Code-like agent harness from scratch, showing how model access is combined with the surrounding code that lets an agent perceive, reason, and act in an environment. It is for people learning to develop real AI agents. The catalogue add-ons support workflows built around this agent harness.

shareAI-lab/learn-claude-code · 78,748 stars · on GitHub · learn.shareai.run

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.

Any agent
npx skills add shareAI-lab/learn-claude-code --skill code-review
Clone the repo
git clone --depth 1 https://github.com/shareAI-lab/learn-claude-code

Made for: Claude Code, Codex.

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

README.md
[![agentmods](https://agentmods.dev/badge/skills/shareai-lab/learn-claude-code/code-review/github.svg)](https://agentmods.dev/skills/shareai-lab/learn-claude-code/code-review)
Your own site
<a href="https://agentmods.dev/skills/shareai-lab/learn-claude-code/code-review"><img src="https://agentmods.dev/badge/skills/shareai-lab/learn-claude-code/code-review/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

Your own site · 80×15
<a href="https://agentmods.dev/skills/shareai-lab/learn-claude-code/code-review"><img src="https://agentmods.dev/badge/skills/shareai-lab/learn-claude-code/code-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 35 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,103 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe. ✓ AI security review Fable 5.1 · 6 Sept 2026 📄 Read the review Third-party audits
  • Snyk pass 7 Sept 2026
  • 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 $0.00035 $0.01103
Opus 5.5 $0.00014 $0.00441
Sonnet 5.5 $0.00007 $0.00221
Haiku 4.5 $0.00003 $0.00110

Measured 1mo ago against content hash a64c8c43b496, 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 scanned grade A with 1 finding 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.

Runs shell commandslowCapability

Expected in a hook, worth knowing in a rule or an instructions file.

os.system(f"ls {user_input}")
Origin

Copies of this mod

8 near-identical copies found in the catalogue:

skills/code-review/SKILL.md · 158 lines

How it starts

The opening of the file, as written. The whole thing — 158 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Code Review Skill

You now have expertise in conducting comprehensive code reviews. Follow this structured approach:

Review Checklist

1. Security (Critical)

Check for:

  • Injection vulnerabilities: SQL, command, XSS, template injection
  • Authentication issues: Hardcoded credentials, weak auth
  • Authorization flaws: Missing access controls, IDOR
  • Data exposure: Sensitive data in logs, error messages
  • Cryptography: Weak algorithms, improper key management
  • Dependencies: Known vulnerabilities (check with npm audit, pip-audit)
# Quick security scans
npm audit                    # Node.js
pip-audit                    # Python
cargo audit                  # Rust
grep -r "password\|secret\|api_key" --include="*.py" --include="*.js"

2. Correctness

Check for:

  • Logic errors: Off-by-one, null handling, edge cases
  • Race conditions: Concurrent access without synchronization
  • Resource leaks: Unclosed files, connections, memory
  • Error handling: Swallowed exceptions, missing error paths
  • Type safety: Implicit conversions, any types

3. Performance

Check for:

  • N+1 queries: Database calls in loops
  • Memory issues: Large allocations, retained references
  • Blocking operations: Sync I/O in async code
  • Inefficient algorithms: O(n^2) when O(n) possible
  • Missing caching: Repeated expensive computations

4. Maintainability

Check for:

  • Naming: Clear, consistent, descriptive
  • Complexity: Functions > 50 lines, deep nesting > 3 levels
  • Duplication: Copy-pasted code blocks
  • Dead code: Unused imports, unreachable branches
  • Comments: Outdated, redundant, or missing where needed

5. Testing

Check for:

  • Coverage: Critical paths tested
  • Edge cases: Null, empty, boundary values
  • Mocking: External dependencies isolated
  • Assertions: Meaningful, specific checks

Read the full file on GitHub · 158 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 · 158 lines · 35 tokens per session scan A a64c8c43b496

Subscribe to this mod's changes

code-review is a skill published in the GitHub repository shareAI-lab/learn-claude-code (78,748 stars, last pushed 19d ago), licensed MIT. It adds 35 tokens to every session and 1,103 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 1 finding (runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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