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 marduk191/qwen3_mcp --skill code-reviewgit clone --depth 1 https://github.com/marduk191/qwen3_mcpWrote 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/marduk191/qwen3_mcp/code-review)<a href="https://agentmods.dev/skills/marduk191/qwen3_mcp/code-review"><img src="https://agentmods.dev/badge/skills/marduk191/qwen3_mcp/code-review.svg" alt="Measured on agentmods" 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 | $0.00000 | $0.00375 |
| Opus 5 | $0.00000 | $0.00187 |
| Sonnet 5 | $0.00000 | $0.00075 |
| Haiku 4.5 | $0.00000 | $0.00038 |
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 8d 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.
What it actually says
Code Review Skill
A skill that teaches the AI how to perform thorough code reviews.
Instructions
When asked to review code, follow this systematic approach:
1. First Pass - Overview
- Understand the purpose of the code
- Check file/module organization
- Identify the main logic flow
2. Code Quality Checks
- Naming: Variables, functions, and classes should have clear, descriptive names
- DRY: Look for duplicated code that could be refactored
- SOLID: Check adherence to SOLID principles where applicable
- Complexity: Flag overly complex functions (cyclomatic complexity)
3. Security Review
- Check for SQL injection vulnerabilities
- Look for XSS vulnerabilities in web code
- Identify hardcoded secrets or credentials
- Check input validation and sanitization
4. Performance
- Identify N+1 query problems
- Look for unnecessary loops or iterations
- Check for memory leaks or unbounded growth
- Review async/await usage
5. Error Handling
- Ensure errors are properly caught and handled
- Check for bare except/catch blocks
- Verify error messages are helpful but not leaky
6. Testing
- Check test coverage
- Identify untested edge cases
- Review test quality and assertions
Output Format
Provide your review in this format:
## Summary
[Brief overall assessment]
## Critical Issues 🔴
[Must-fix problems]
## Warnings 🟡
[Should-fix problems]
## Suggestions 🟢
[Nice-to-have improvements]
## Good Practices ✅
[Things done well - positive feedback]
Example Usage
User: "Review this Python code for me" Assistant: Uses this skill's methodology to provide structured review
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.
- 8d ago First seen · 67 lines · 0 tokens per session scan A de0ecd1cd5a2
code-review is a skill published in the GitHub repository marduk191/qwen3_mcp (13 stars, last pushed 7mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 375 tokens. 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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