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 teachgit 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/teach)<a href="https://agentmods.dev/skills/vinvcn/mattpocock-skills-zh-cn/teach"><img src="https://agentmods.dev/badge/skills/vinvcn/mattpocock-skills-zh-cn/teach/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/teach"><img src="https://agentmods.dev/badge/skills/vinvcn/mattpocock-skills-zh-cn/teach.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- 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 | $0.00016 | $0.02003 |
| Opus 5.5 | $0.00006 | $0.00801 |
| Sonnet 5.5 | $0.00003 | $0.00401 |
| Haiku 4.5 | $0.00002 | $0.00200 |
Grade A, and why
teach 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 18d 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 — 141 lines — stays where its author put it; the contents beside it link to each section on GitHub.
用户要求你教他们某件事。这是一个 stateful request:他们打算在多个 sessions 中学习这个 topic。
教学工作区
把当前目录视为 teaching workspace。他们的学习状态保存在这个目录中的几个文件里:
MISSION.md:记录用户为什么对这个 topic 感兴趣。所有教学都应以它为 grounding。使用 MISSION-FORMAT.md 中的格式。./reference/*.html:reference materials 目录。这些是从 lessons 中压缩出的 learnings:cheat sheets、reference algorithms、syntax、yoga poses、glossaries。它们是原始学习单元。它们应该是漂亮的 documents,适合打印,并为 quick reference 设计。RESOURCES.md:可探索的 resources 列表,用来把教学建立在 context knowledge 上,或获取 knowledge 和 wisdom。使用 RESOURCES-FORMAT.md 中的格式。./learning-records/*.md:learning records 目录,记录用户已经学到的东西。它们大致相当于软件开发里的 architectural decision records:捕获非显而易见的 lessons 和 key insights,这些内容可能之后需要修订,或推动未来 sessions。它们应用来计算 zone of proximal development。标题格式为0001-<dash-case-name>.md,数字每次递增。使用 LEARNING-RECORD-FORMAT.md 中的格式。./lessons/*.html:lessons 目录。一个 lesson 是一个单独、自包含的 HTML output,用来教授一个与 mission 绑定的 tightly-scoped 内容。这是此 workspace 中教学的主要单元。./assets/*:跨 lessons 共享的可复用 components。见 Assets。NOTES.md:scratchpad,用来记下用户偏好或 working notes。
理念
要深度学习,用户需要三样东西:
- Knowledge:从 high-quality、high-trust resources 中获取
- Skills:通过你基于 knowledge 设计的高度相关 interactive lessons 获得
- Wisdom:来自与其他 learners 和 practitioners 的互动
在 RESOURCES.md 还没有充分填充前,你的重点应是寻找能帮助用户获取 knowledge 的高质量 resources。不要相信你的 parametric knowledge。
有些 topics 可能比 knowledge 更需要 skills。学习 theoretical physics 可能更偏 knowledge-based。Yoga 则更偏 skills-based。
Fluency 与 Storage Strength
你应小心区分两类学习:
- Fluency strength:当下提取 knowledge 的能力
- Storage strength:长期保持 knowledge 的能力
Fluency 会给用户一种掌握了的错觉,但 storage strength 才是真正目标。尝试通过 desirable difficulty 设计能建立长期保持的 lessons:
- 使用 retrieval practice(从记忆中 recall)
- Spacing(把 practice 分布在不同时间)
- Interleaving(在 practice 中混合不同但相关的 topics,仅用于 skills practice)
Lessons
Lesson 是你产出的主要东西,也就是 knowledge 和 skills 触达用户的单元。每个 lesson 都是一个自包含 HTML 文件,保存到 ./lessons/,标题为 0001-<dash-case-name>.html,数字每次递增。
What ships with it
5 files 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.
- 18d ago Changed 4cc212bf7aed
- 1mo ago First seen · 141 lines · 16 tokens per session scan A 66b4af52c18e
teach is a skill published in the GitHub repository vinvcn/mattpocock-skills-zh-CN (5,317 stars, last pushed 7d ago), licensed MIT. It adds 16 tokens to every session and 2,003 once invoked, about $0.0001 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 2026-08-30.
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