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 Lion-1209/Lion-Skills --skill code-reviewgit clone --depth 1 https://github.com/Lion-1209/Lion-SkillsWrote 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/lion-1209/lion-skills/code-review)<a href="https://agentmods.dev/skills/lion-1209/lion-skills/code-review"><img src="https://agentmods.dev/badge/skills/lion-1209/lion-skills/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/lion-1209/lion-skills/code-review"><img src="https://agentmods.dev/badge/skills/lion-1209/lion-skills/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 | $0.00023 | $0.02274 |
| Opus 5.5 | $0.00009 | $0.00910 |
| Sonnet 5.5 | $0.00005 | $0.00455 |
| Haiku 4.5 | $0.00002 | $0.00227 |
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.
This is a copy
100% identical to code-review — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 103 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Review
概述
对代码做有重点、分层次的审查——先抓正确性和安全问题,再管可读性,风格交给工具。核心:好的 review 让作者知道"哪里有真问题、该先改什么";坏的 review 是一堆 nit 淹没重点,或一句"看起来不错"放过错误。
何时使用
- 提交前审查自己或别人的代码(自我 review 见下文专门技巧)
- 同事让你看他的 PR
- 不确定 review 该看什么、怎么反馈
不该用:纯风格/格式问题(交给 linter/formatter 自动化,不该占用人 review);想确认"功能对不对"——那是 verify-and-fix(实际跑)的事,review 是静态审查、替代不了运行验证。
与相邻 skill 的边界:code-review 是审查视角(找问题、分严重度、给建议),verify-and-fix 是修复视角(改对、验证)。code-review 发现的问题,需要修的进入 verify-and-fix 流程;review 中发现的"行为不对/报错"可能要先用 debugging 定位根因。三者接力:review 找问题 → debugging 定位 → verify-and-fix 修+验证。
核心内容
正确性优先,别被风格带偏
review 最常见的错是逐行挑风格(命名、缩进、注释多少)而放过正确性(逻辑对不对、边界处理了吗、有没有竞态)。正确性问题会让程序出错,风格问题只是不好看——前者 critical,后者 nit,优先级天差地别。
按重要性排序,review 该查的维度:
- 正确性:逻辑对吗?能跑通预期路径吗?有没有逻辑漏洞?(最该花时间)
- 边界与异常:空值/空集合/零/负数/超大输入怎么处理?外部依赖失败(网络/DB)呢?
- 安全:有没有注入(SQL/命令/XSS)?密码/密钥处理对吗?权限检查到位吗?敏感信息泄露吗?
- 并发:共享状态有竞态吗?异步顺序依赖对吗?资源泄漏(未关闭的连接/锁未释放)?
- 可维护性:命名清不清楚?结构是否过度复杂?有没有重复?(这里才是 nit 的领地)
- 测试:有测试吗?测的是行为还是实现?覆盖了关键路径和边界吗?
前 4 类是"会让程序出错或出事"的,必须查;第 5 类是"让人难受"的,次要;风格细节(缩进/格式)不该人查,交给工具。
按改动性质调整重点:上面是通用清单,但不同代码该重点查的不同——别对所有代码平均用力。涉及钱/库存/计数的,重点查原子性和一致性(中途失败会不会凭空产生/消失);涉及外部输入的(用户输入、API、文件),重点查安全(注入、越权);涉及共享状态/异步的,重点查竞态和资源泄漏;涉及配置/迁移的,重点查回滚和兼容。先识别"这段代码的风险面在哪",把 review 力量集中投到那里。
分严重度,别把 nit 和 critical 混着
review 反馈必须分严重度,让作者知道先改什么:
- 阻塞(blocking / critical):必须改才能合并——逻辑错、安全漏洞、会崩溃、数据丢失风险。
- 重要(important):强烈建议改——边界没处理、缺少测试、设计有隐患,但不阻塞本次合并。
- 建议(nit / suggestion):可选——命名、可读性、小重构。改了更好,不改也能过。
不分层的 review 有两种失败:把 nit 当 critical(作者被一堆小事压垮,反而漏改真问题)、把 critical 当 nit(真问题被淹没在风格意见里)。nit 要克制——堆 15 条 nit 是在浪费作者时间,把同类 nit 归并成一条"风格建议",或直接交给 linter。
反馈要带依据和建议,不只是"这不好"
每条 review 意见应该让作者能理解问题 + 知道怎么改:
- 指出问题 + 为什么是问题:不说"这写得不好",说"
user.name在 user 为 null 时会抛 TypeError——db.find 找不到时返回 null"。 - 给方向或示例:不只说"改一下",给"加个 null 检查,找不到时抛业务错误或返回 null,看调用方期望"。
- 区分事实和偏好:"这里有 null 风险"(事实,基于代码)vs "我觉得该用 early return"(偏好,标注是建议)。
带依据的反馈让作者能判断对错、学到东西;空泛的"不好"让作者只能盲从或抵触。
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 · 103 lines · 23 tokens per session scan A d60a60059723
code-review is a skill published in the GitHub repository Lion-1209/Lion-Skills (5 stars, last pushed 3mo ago), licensed MIT. It adds 23 tokens to every session and 2,274 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to code-review, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
review-pubsub-subscriptions
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review-agent-tools
Reviews agent tool implementations for idempotency, input validation, docstring quality and conventions. Use for "review agent tools" or "check tool idempotency".
review-workflow-management
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review-pubsub-components
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review-pubsub-publishing
Reviews Dapr pub/sub publishing code in .NET and Python for swallowed publish failures, wrong pub/sub names, content types, client lifetime, bulk-publish partial failures and payload size. Use for "review my pub/sub publishing code" or "audit Dapr publish calls".
review-agent-orchestration
Reviews multi-agent orchestration for pub/sub topic conventions, loop safety and handoff correctness. Use for "review agent orchestration" or "check multi-agent handoffs".