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 muyuhill/100books-to-skills --skill show-your-workgit clone --depth 1 https://github.com/muyuhill/100books-to-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/muyuhill/100books-to-skills/show-your-work)<a href="https://agentmods.dev/skills/muyuhill/100books-to-skills/show-your-work"><img src="https://agentmods.dev/badge/skills/muyuhill/100books-to-skills/show-your-work/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/muyuhill/100books-to-skills/show-your-work"><img src="https://agentmods.dev/badge/skills/muyuhill/100books-to-skills/show-your-work.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 | $0.00069 | $0.00934 |
| Opus 5 | $0.00034 | $0.00467 |
| Sonnet 5 | $0.00014 | $0.00187 |
| Haiku 4.5 | $0.00007 | $0.00093 |
Grade A, and why
show-your-work 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 12d 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
Show Your Work — 10 条创作者自我营销法则
你不用是天才才配分享。你只需要持续展示你的创作过程，让别人看到你在做什么。
Austin Kleon 的 10 条法则，每一条都是对「等完美了再发」的反击。
法则一：你不用是天才（You Don't Have to Be a Genius）
不用当专家，当个「业余爱好者」——一个愿意公开学习过程的人。
业余爱好者的优势：刚学会的东西，最清楚别人哪里会卡住。专家的盲区恰恰是他已经忘了新手的感觉。
法则二：思考过程，而非产品（Think Process, Not Product）
人们不只是对成品感兴趣——他们对「你怎么做出来的」更感兴趣。
把你工作的过程拍下来、写下来、发出去。草图、废稿、纠结——都是内容。成品是结果，过程是故事。
法则三：每天分享一点（Share Something Small Every Day）
每天发一小块——一篇文章、一张图、一个想法。不需要长篇大论。
频率 > 单篇质量。每天出现一次的人比偶尔发一篇爆款的人更让人记住。
法则四：打开你的「奇珍柜」（Open Up Your Cabinet of Curiosities）
分享你正在看的东西——书、文章、工具、想法。你不只是创作者，你是策展人。
不只分享你做的，也分享你喜欢的。推荐别人的好作品不会抢走你的观众——会让你成为信息枢纽。
法则五：讲好故事（Tell Good Stories）
作品不会自己说话。你得给它配上故事——创作背后的动机、过程、偶然。
好的故事公式：我遇到了什么问题 → 我是怎么尝试解决的 → 结果是什么 → 你也能试试。
法则六：教别人你刚学会的东西（Teach What You Know）
刚学会的东西，立刻教给别人。教学是最强的学习方式。
不要等到成为专家再教——教的过程就是你变专家的过程。
法则七：不要变成人肉垃圾邮件（Don't Turn Into Human Spam）
推广自己不是刷屏发链接。是给别人价值，再提自己。
80% 给价值，20% 提自己。在别人的评论区认真回复比发 10 条自嗨帖有效。
法则八：学会挨打（Learn to Take a Punch）
公开分享就会有人批评。把批评分成两类：有用的和无用的。只在意前者。
不要因为害怕负评就不发。不发才是唯一的失败。
法则九：卖出去（Sell Out）
当你有了观众，可以开始收钱。卖东西不是出卖灵魂——是你劳动的回报。
在你有 1000 个真正喜欢你的人之后，任何一个产品都能养活你。
法则十：坚持下去（Stick Around）
成功不是一夜之间的，是不放弃的结果。大多数人放弃不是因为失败，是因为无聊。
坚持公开分享三年。三年后回头看，你会感谢那个没放弃的自己。
一句话总结
你不用等到准备好了才分享。你现在在做什么、在学什么——把它公开。那就是你的个人品牌。
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.
- 12d ago First seen · 102 lines · 69 tokens per session scan A cb37fc3fb133
show-your-work is a skill published in the GitHub repository muyuhill/100books-to-skills (12 stars, last pushed 2mo ago), licensed MIT. It adds 69 tokens to every session and 934 once invoked, about $0.0003 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.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
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…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…