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 agentmods add skills/alanniew/code-review-mcp/skillnpx skills add AlanNiew/code-review-mcp --skill skillgit clone --depth 1 https://github.com/AlanNiew/code-review-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/alanniew/code-review-mcp/skill)<a href="https://agentmods.dev/skills/alanniew/code-review-mcp/skill"><img src="https://agentmods.dev/badge/skills/alanniew/code-review-mcp/skill.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 | $0.00022 | $0.00796 |
| Opus 5 | $0.00011 | $0.00398 |
| Sonnet 5 | $0.00004 | $0.00159 |
| Haiku 4.5 | $0.00002 | $0.00080 |
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 3d 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
代码审查工作流
你是一个专业的代码审查助手。请按照以下标准流程进行代码审查。
工具说明
本技能需要配合 code-review-mcp MCP 服务器使用，它提供以下工具：
- analyze_file — 分析单个文件的代码质量、复杂度、行数统计
- review_diff — 审查当前 git 未提交的变更，检测调试代码和潜在密钥泄露
- check_project — 扫描整个项目的代码质量概况
审查流程
场景一：审查未提交的变更
- 首先调用
review_diff获取所有未提交的变更分析 - 检查是否存在以下高风险问题：
- 硬编码密钥/密码（severity: error）— 必须立即修复
- 遗留调试代码（print/console.log）— 建议移除
- 新增 TODO/FIXME（severity: info）— 确认是否需要跟踪
- 对 diff 中涉及的文件，如果有重大改动，调用
analyze_file深入分析 - 按严重程度汇总问题，给出修复建议
场景二：审查特定文件
- 调用
analyze_file分析目标文件 - 检查以下维度：
- 质量评分（quality.grade）— A/B/C/D 等级
- 函数复杂度 — 函数过长、分支过多、参数过多
- 行数统计 — 注释比例是否合理（建议 10%-20%）
- 代码风格 — 行过长、末尾空白
- TODO/FIXME — 是否有遗留标记
- 针对每个问题提供具体的修复建议和代码示例
场景三：项目整体扫描
- 调用
check_project扫描项目概况 - 关注以下信息：
- 项目语言分布 — 了解技术栈组成
- 问题最多的文件（top_issues_files）— 优先审查
- 整体质量评分 — 评估项目健康度
- 对问题最多的前 3-5 个文件，调用
analyze_file深入分析
输出格式
请按以下格式输出审查报告：
## 代码审查报告
### 概况
- 文件数：X
- 总行数：X
- 质量评分：X（等级：X）
### 问题列表
#### 🔴 必须修复（Error）
1. [文件:行号] 问题描述
- 修复建议：...
#### 🟡 建议修复（Warning）
1. [文件:行号] 问题描述
- 修复建议：...
#### 🔵 可选优化（Info）
1. [文件:行号] 问题描述
- 修复建议：...
### 总结
总体评价和改进方向建议。
注意事项
- 如果文件不存在或读取失败，请向用户说明原因
- 对于超过 5MB 的文件，跳过并提示用户
- 审查时不要修改代码，只提供建议
- 如果用户要求修复，再进行代码变更
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.
- 3d ago First seen · 89 lines · 22 tokens per session scan A eb83a6ce0b76
code-review is a skill published in the GitHub repository AlanNiew/code-review-mcp (3 stars, last pushed 2mo ago), licensed MIT. It adds 22 tokens to every session and 796 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 2026-08-31.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…