mattpocock-skills-zh-CN is a Simplified Chinese localization of a collection of reusable instructions for coding agents. Chinese-speaking developers use the translated skills to support engineering workflows while keeping their original commands, paths, identifiers, and behavior. The catalogue contains the localized skills, instructions, and plugin components.
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 vinvcn/mattpocock-skills-zh-CN --skill code-reviewgit clone --depth 1 https://github.com/vinvcn/mattpocock-skills-zh-CNWrote 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/vinvcn/mattpocock-skills-zh-cn/code-review)<a href="https://agentmods.dev/skills/vinvcn/mattpocock-skills-zh-cn/code-review"><img src="https://agentmods.dev/badge/skills/vinvcn/mattpocock-skills-zh-cn/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/vinvcn/mattpocock-skills-zh-cn/code-review"><img src="https://agentmods.dev/badge/skills/vinvcn/mattpocock-skills-zh-cn/code-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
- NVIDIA SkillSpector pass
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 | $0.00094 | $0.01577 |
| Opus 5 | $0.00047 | $0.00788 |
| Sonnet 5 | $0.00019 | $0.00315 |
| Haiku 4.5 | $0.00009 | $0.00158 |
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 11d 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 — 88 lines — stays where its author put it; the contents beside it link to each section on GitHub.
对用户提供的 fixed point 与 HEAD 之间的 diff 做双轴 review:
- Standards — 代码是否符合这个 repo 记录下来的 coding standards?
- Spec — 代码是否忠实实现来源 issue / spec?
两个轴线都作为并行 sub-agents运行,避免互相污染 context;然后这个 skill 聚合它们的 findings。
Issue tracker 应该已经提供给你;如果缺少 docs/agents/issue-tracker.md,运行 /setup-matt-pocock-skills。
Process
1. Pin the fixed point
用户说的任何内容都是 fixed point:commit SHA、branch name、tag、main、HEAD~5 等。如果用户没有指定,就询问。
先捕获一次 diff command:git diff <fixed-point>...HEAD(three-dot,因此比较对象是 merge-base)。同时用 git log <fixed-point>..HEAD --oneline 记录 commits 列表。
继续前,确认 fixed point 能解析(git rev-parse <fixed-point>),并且 diff 非空。错误 ref 或空 diff 应该在这里失败,而不是进入两个并行 sub-agents 后才失败。
2. Identify the spec source
按以下顺序寻找来源 spec:
- Commit messages 中的 issue references(
#123、Closes #45、GitLab!67等)— 按docs/agents/issue-tracker.md中的 workflow 获取。 - 用户作为 argument 传入的 path。
docs/、specs/或.scratch/下与 branch name 或 feature 匹配的 spec 文件。- 如果什么都找不到,询问用户 spec 在哪里。如果用户说没有 spec,Spec sub-agent 跳过并报告 “no spec available”。
3. Identify the standards sources
Repo 中任何记录代码应该如何写的内容,例如 CODING_STANDARDS.md 或 CONTRIBUTING.md。
在 repo 自己记录的 standards 之外,Standards 轴线始终带有下面的 smell baseline:一组固定的 Fowler code smells(Refactoring 第 3 章),即使 repo 没有任何约定也适用。有两条规则:
- The repo overrides. 已记录的 repo standard 永远优先;如果它认可 baseline 会标记的东西,就压制该 smell。
- Always a judgement call. 每个 smell 都是带 label 的 heuristic(例如 "possible Feature Envy"),不是硬性违规;和这里的其他 standard 一样,跳过 tooling 已经强制检查的内容。
每个 smell 按 what it is -> how to fix 读取,并对照 diff:
- Mysterious Name — function、variable 或 type 的名称没有说明它做什么或装什么。-> rename it;如果找不到诚实名称,设计本身可能浑浊。
- Duplicated Code — 同一 logic shape 出现在多个 hunk 或 file 中。-> 抽出共享形状,让两边调用。
- Feature Envy — method 访问另一个 object 的 data 多于自己的 data。-> 把 method 移到它羡慕的数据上。
- Data Clumps — 同几组 fields 或 params 总是一起出现。-> 包成一个 type 来传。
- Primitive Obsession — primitive 或 string 代替了值得拥有自有 type 的 domain concept。-> 给该 concept 一个小 type。
- Repeated Switches — 对同一 type 的相同
switch/ifcascade 在改动中重复。-> 换成 polymorphism,或共享一个 map。 - Shotgun Surgery — 一个 logical change 迫使 diff 分散修改很多文件。-> 把一起变化的东西收拢进一个 module。
- Divergent Change — 一个 file 或 module 因多个无关原因被修改。-> 拆分,让每个 module 只因一个原因变化。
- Speculative Generality — 为 spec 没有的需求增加 abstraction、params 或 hooks。-> 删除它,inline 回来,直到有真实需要。
- Message Chains — caller 不该依赖的长链式导航
a.b().c().d()。-> 把这段导航藏到第一个 object 的一个 method 后面。 - Middle Man — class 或 function 基本只是在继续委托。-> 删掉它,直接调用真实目标。
- Refused Bequest — subclass 或 implementer 忽略或 override 了继承来的大部分内容。-> 去掉 inheritance,使用 composition。
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.
- 11d ago First seen · 88 lines · 94 tokens per session scan A 36ef136c3863
code-review is a skill published in the GitHub repository vinvcn/mattpocock-skills-zh-CN (4,114 stars, last pushed 4d ago), licensed MIT. It adds 94 tokens to every session and 1,577 once invoked, about $0.0005 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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