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 copywriting-secretsgit 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/copywriting-secrets)<a href="https://agentmods.dev/skills/muyuhill/100books-to-skills/copywriting-secrets"><img src="https://agentmods.dev/badge/skills/muyuhill/100books-to-skills/copywriting-secrets/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/copywriting-secrets"><img src="https://agentmods.dev/badge/skills/muyuhill/100books-to-skills/copywriting-secrets.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 | $0.00068 | $0.00485 |
| Opus 5 | $0.00034 | $0.00243 |
| Sonnet 5 | $0.00014 | $0.00097 |
| Haiku 4.5 | $0.00007 | $0.00049 |
Grade A, and why
copywriting-secrets 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
Copywriting Secrets — 文案写作公式
好的文案不是写出来的——是套公式套出来的。
Russell Brunson 的文案公式：标题 → 子弹点 → 行动号召。
核心公式：AIDA
Attention（注意力）→ Interest（兴趣）→ Desire（欲望）→ Action（行动）
| 阶段 | 做什么 | 怎么写 |
|---|---|---|
| Attention | 标题/第一句让人停下来 | 用痛点/好奇心/数字 |
| Interest | 让他们想继续看 | 讲一个跟他们有关的故事 |
| Desire | 让他们想要你的产品 | 列出好处——不是功能，是「用了之后怎样」 |
| Action | 让他们采取行动 | 明确的、低门槛的指令 |
标题公式
- 「如何 [得到想要的结果] 而不 [不想付出的代价]」
- 「[数字] 种 [方法] 让你 [得到结果]」
- 「为什么 [常见做法] 是错误的——以及该怎么做的真相」
子弹点（Bullet Points）
不要列功能，列「得到的好处」：
- ✘ 「内置 AI 引擎」
- ✔ 「你不需要自己写一个字——AI 帮你生成整篇初稿」
一句话总结
人们不买产品，买的是「用了之后会变怎样」。你的文案只需要回答一个问题：用了我这个，你会变成什么样？
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 · 53 lines · 68 tokens per session scan A b51ac829c3e3
copywriting-secrets is a skill published in the GitHub repository muyuhill/100books-to-skills (12 stars, last pushed 2mo ago), licensed MIT. It adds 68 tokens to every session and 485 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…