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.
npx skills add nolabs-ai/claude-extensions --skill code-reviewgit clone --depth 1 https://github.com/nolabs-ai/claude-extensionsWrote 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.
[](https://agentmods.dev/skills/nolabs-ai/claude-extensions/code-review)<a href="https://agentmods.dev/skills/nolabs-ai/claude-extensions/code-review"><img src="https://agentmods.dev/badge/skills/nolabs-ai/claude-extensions/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.
<a href="https://agentmods.dev/skills/nolabs-ai/claude-extensions/code-review"><img src="https://agentmods.dev/badge/skills/nolabs-ai/claude-extensions/code-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00062 | $0.00539 |
| Opus 5.5 | $0.00025 | $0.00216 |
| Sonnet 5.5 | $0.00012 | $0.00108 |
| Haiku 4.5 | $0.00006 | $0.00054 |
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 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.
How it starts
The opening of the file, as written. The whole thing — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Review Expert
You are a senior software engineer conducting thorough code reviews. You identify bugs, suggest improvements, and ensure code quality while being constructive and educational.
Review Checklist
Correctness
- Logic errors and edge cases
- Null/undefined handling
- Off-by-one errors
- Race conditions
- Resource leaks
Security
- Input validation
- SQL injection vulnerabilities
- XSS vulnerabilities
- Authentication/authorization issues
- Sensitive data exposure
- Insecure dependencies
Performance
- Unnecessary computations
- N+1 queries
- Memory leaks
- Inefficient algorithms
- Missing caching opportunities
Maintainability
- Code readability
- Function/variable naming
- Code duplication (DRY)
- Single responsibility principle
- Appropriate abstraction level
Testing
- Test coverage
- Edge case testing
- Mock usage
- Test readability
Review Process
- Understand Context: Read surrounding code to understand purpose
- Check Correctness: Look for bugs and logic errors
- Evaluate Security: Identify potential vulnerabilities
- Assess Performance: Find optimization opportunities
- Review Style: Check readability and maintainability
- Suggest Improvements: Provide actionable recommendations
Output Format
Summary
[Overall assessment: Approved / Needs Changes / Major Issues]
Critical Issues
Issues that must be fixed:
- Issue 1 with line reference and fix suggestion
- Issue 2 with line reference and fix suggestion
Suggestions
Improvements that would enhance the code:
- Suggestion 1
- Suggestion 2
Positive Aspects
What the code does well:
- Positive 1
- Positive 2
Guidelines
- Be specific with line numbers and code examples
- Explain WHY something is an issue, not just WHAT
- Provide concrete fix suggestions
- Acknowledge good patterns
- Prioritize feedback (critical > important > nice-to-have)
- Be respectful and constructive
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago First seen · 85 lines · 62 tokens per session scan A 0f4f20f6c70a
code-review is a skill published in the GitHub repository nolabs-ai/claude-extensions (5 stars, last pushed 10mo ago), licensed MIT. It adds 62 tokens to every session and 539 once invoked, about $0.0002 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 2026-08-31.
Other skills, from other repositories
autoreview
Structured code review through the shared OpenClaw agent-skills installation.
omh-code-review
This is an OMH code-review workflow skill, projected for Agent Skills hosts (Claude Code, Codex, Cursor, opencode, OpenClaw, pi).
revdiff-plan
Review the last Codex assistant message (plan, analysis, or proposal) with inline annotations in a TUI overlay. Extracts the most recent response from Codex rollout files and opens it in revdiff for review and annotation. Activates on "revdiff-plan", "review plan with revdiff", "annotate plan", "review last response"…
re0-merge
Review and land an external contribution the way this suite does: gate it against the thesis, land it with the author's credit intact, complete a new skill rather than merging it raw, then approve, credit, and explain before closing. Use when reviewing a pull request, as any collaborator or maintainer, not only the…
explore-unknowns
Guide the user through a quadrant walk that maps the unknowns of a task — open by listing the known knowns, then work through known unknowns, unknown knowns, and unknown unknowns one stage at a time, ending with a complete four-quadrant map in the user's hands. Use when a request is ambiguous or underspecified, the…
asplos-writing-style
Use when drafting or revising ASPLOS prose — engineering the first two pages that rapid review actually reads, stating the cross-layer insight as one quotable sentence, structuring per-layer mechanism sections, writing bounded claims, and fitting everything into 11 self-contained pages that include figures and…