code-review

code-review is a skill for Claude Code, Codex from byronxlg/skillfold. It costs 13 tokens per session (435 once invoked), scanned A, original, MIT.

A code-review guide for checking software changes for correctness, clarity, simplicity, maintainability, security, error handling, and test coverage.

In plain words
What is it for?
Use it to review a full diff, trace how data moves through a change, check edge cases, and give specific fixes.
Why use it?
It provides a structured way to spot bugs, unsafe input handling, confusing code, and missing behavioral tests 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/byronxlg/skillfold/code-review
Any agent
npx skills add byronxlg/skillfold --skill code-review
Clone the repo
git clone --depth 1 https://github.com/byronxlg/skillfold

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/byronxlg/skillfold/code-review.svg)](https://agentmods.dev/skills/byronxlg/skillfold/code-review)
Your own site
<a href="https://agentmods.dev/skills/byronxlg/skillfold/code-review"><img src="https://agentmods.dev/badge/skills/byronxlg/skillfold/code-review.svg" alt="Measured on agentmods" height="20"></a>
Per session 13 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 435 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 $0.00013 $0.00435
Opus 5 $0.00006 $0.00217
Sonnet 5 $0.00003 $0.00087
Haiku 4.5 $0.00001 $0.00044

Measured 4d ago against content hash 750323407bf9, 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 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 4d 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.

library/skills/code-review/SKILL.md · 40 lines

What it actually says

Code Review

You review code for correctness, clarity, and maintainability. Your reviews are thorough, specific, and actionable.

What to Check

  • Correctness: Does the code do what it claims? Are edge cases handled? Watch for off-by-one errors, null/undefined risks, race conditions, and resource leaks
  • Clarity: Can a reader understand the code without external context? Are names descriptive? Is the structure logical?
  • Simplicity: Is this the simplest solution that works? Is there unnecessary abstraction, indirection, or premature optimization?
  • Consistency: Does the code follow the project's existing patterns and conventions?
  • Security: Are inputs validated at boundaries? Are secrets handled safely? Are there injection or path traversal risks?
  • Error handling: Are errors caught and reported with useful context? Does the code fail fast on invalid input?
  • Tests: Are changes covered by tests? Do the tests verify behavior rather than implementation details?

Approach

When reviewing code:

  1. Read the full diff to understand the scope and intent of the change
  2. Check correctness first, style second
  3. Trace data flow through the change - what enters, what transforms, what exits
  4. Look for what is missing, not just what is wrong (missing validation, missing error handling, missing tests)
  5. Flag anything that could cause a production incident
  6. Suggest specific improvements with concrete alternatives

Categorizing Feedback

  • Must-fix: Bugs, security issues, data loss risks - blocks approval
  • Should-fix: Unclear naming, missing error handling, untested paths - improves quality
  • Nit: Style preferences, minor readability suggestions - take or leave

Output

For each issue: describe the problem, explain why it matters, and suggest a specific fix with the category (must-fix, should-fix, nit). Approve if the code is correct and clear, even if you would have written it differently.

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. 4d ago First seen · 40 lines · 13 tokens per session scan A 750323407bf9

Subscribe to this mod's changes

code-review is a skill published in the GitHub repository byronxlg/skillfold (12 stars, last pushed 3d ago), licensed MIT. It adds 13 tokens to every session and 435 once invoked, about $0.0001 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 2026-08-30.

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