
book-to-skill
Skill把技术书、文档目录或论文集(PDF、EPUB、DOCX、Markdown 等)提炼成 agent 技能:核心框架、按需加载的章节文件、术语表与速查表,工作中随时调用查阅。抽取脚本需本机 Python,PDF 可选装 poppler 或 docling。
book-to-skill
Turn any technical book, document folder, or collection of sources into a unified agent skill — ready to study, reference, and use while you work in GitHub Copilot CLI, Amp, Claude Code, Codex, Hermes Agent, OpenCode, or OpenClaw.
Why · What it generates · Beyond books · How it works · Usage · Install · FAQ · Performance · Architecture · Changelog
24×–51× fewer tokens than dumping the book into context to answer one question, measured on real books (how it's measured).
How it works, in 3 steps:
- Point it at a file, folder, or glob —
/book-to-skill ./my-book.pdf - It distills the book into a skill — frameworks, decision rules, anti-patterns, and per-chapter files. Structure, not a summary.
- Your agent loads it on demand — ask
/my-book replicationand it reads the right chapter and answers from the real content, no hallucination.
🤔 Why
You buy a great technical book. You read it once. Three months later you can't remember chapter 7 existed.
The usual workarounds don't help:
- 📄 "Let me just search the PDF" → you get a list of pages, not answers
- 🧠 "I'll ask the agent about this book" → it either hallucinates or says it doesn't have the content
- 📝 "I'll take notes as I read" → you end up with a 200-line doc you never open again
book-to-skill solves this by turning the book into a structured skill your agent loads on demand.
Once installed, you just type /your-book-slug replication and the agent reads the right chapter and answers from the actual content. No hallucination. No digging through PDFs. The book becomes part of your workflow.
Works with any host that supports the open Agent Skills standard — GitHub Copilot CLI, Amp, Claude Code, Codex, Hermes Agent, OpenCode, and OpenClaw all read the same SKILL.md format.
📦 What it generates
Running /book-to-skill your-book.pdf (or a folder, glob, or list of files) creates a full skill in the user-level cross-agent skills directory ~/.agents/skills/<slug>/ — one copy that Copilot CLI, Amp, Codex, OpenCode, and OpenClaw discover natively (OpenCode also reads its own managed root ~/.config/opencode/skills/<slug>/; OpenClaw also discovers it when using its default state directory, with a non-default OPENCLAW_STATE_DIR use the active state's skills/ root instead). When run under Claude Code, the converter also attempts a verified symlink at ~/.claude/skills/<slug>/ — Claude Code sees the skill when the link read-back confirms it; otherwise the run report says so. Hermes Agent partitions its personal skills by category and does not scan the cross-agent root, so a Hermes install lands in /skills/<category>/<slug>/ instead. OpenClaw-managed, OpenCode-managed, and project-local destinations remain available when explicitly requested:
| File | Purpose | Size |
|---|---|---|
SKILL.md | Core mental models + chapter index | ~4,000 tokens |
chapters/ch01-*.md … | One file per chapter, loaded on-demand | ~1,000 tokens each |
glossary.md | Every key term, alphabetically sorted with chapter refs | ~1,500 tokens |
patterns.md | All techniques, algorithms, and design patterns | ~2,000 tokens |
cheatsheet.md | Decision tables and quick-reference rules | ~1,000 tokens |
Chapter files are loaded on-demand — they don't count against the skill budget until you ask about that topic.
🏢 Beyond books
The name says "book", but the input is any structured prose. The same extraction works on knowledge you own and re-read constantly:
- Internal documentation — architecture decision records, runbooks, onboarding guides. Fold a whole
docs/folder into one skill and ask it while you code. - Brand & design systems — voice guidelines, tone-of-voice docs, component principles. Turn a brand book into a skill your team queries instead of skimming a 60-page PDF.
- Research clusters — a stack of papers plus your own notes, merged into a single unified skill and updated as new material lands (see Update / fold-in).
- Specs & standards — RFCs, API contracts, compliance docs you reference but never memorize.
If you re-open a document often enough to wish you'd memorized it, it's a candidate.
🧾 The Discovery Loop Tax
A PDF-reading agent doesn't just read — it navigates: it re-fetches the ToC, backtracks, and re-processes all of it on every turn. book-to-skill pays that structuring cost once, at conversion, so queries stay proportional to the answer — 24×–51× fewer tokens than dumping the book into context, measured on real books.
📊 Full methodology, numbers, and per-book tables → docs/performance.md
⚙️ How it works
Two halves: a deterministic Python extractor (document → clean text + metadata) and a spec-driven generator (your agent follows SKILL.md to turn that into a structured skill). On-demand chapter files keep the loaded skill small.
🔧 Full walkthrough (Steps 0–10, extraction modes, token budgets) → docs/how-it-works.md
🚀 Usage
/book-to-skill <path|folder|glob> [skill-name] — plus analyze-only, generate-from-analysis, and update/fold-in modes. After a conversion, the converter can publish the skill to GitHub (private by default) so any host installs it with npx skills add.
▶️ All modes and examples → docs/usage.md
💬 In practice → use cases — a DevEx book became a survey of 300+ engineers; a scanned PDF that stalled became #130. Add yours: the account lives in your own Gist, the index takes a one-line PR.
📥 Install
# One command, any host — via the cross-agent skills CLI:
npx skills add virgiliojr94/book-to-skill
# Or manually — clone into your skills folder (registers /book-to-skill):
git clone https://github.com/virgiliojr94/book-to-skill.git ~/.claude/skills/book-to-skill
# (Copilot CLI: ~/.copilot/skills/ · Amp/cross-agent: ~/.agents/skills/)
# (Hermes Agent: ${HERMES_HOME:-$HOME/.hermes}/skills/<category>/)
# (OpenClaw: ${OPENCLAW_STATE_DIR:-$HOME/.openclaw}/skills/; ~/.agents/skills/ only with default state)
# (OpenCode: ~/.agents/skills/ — it also reads ~/.config/opencode/skills/)
📥 All hosts, optional extractors, and the standalone CLI → docs/install.md
❓ FAQ
Common questions — "why not just dump the PDF?", cost, privacy, non-book inputs, multi-file books.
❓ Answers → docs/faq.md
🔧 Requirements
The extractor tries tools in order per format and uses the first available. If nothing is installed, it tells you which command to run. Plain text, Markdown, reStructuredText and AsciiDoc need no extra deps.
Check your setup in one command:
python3 scripts/extract.py --checkprints which extractors are installed for every format and the exact command to install anything missing — no file needed.
PDF — choose by book type:
| Book type | Tool | Install | Speed |
|---|---|---|---|
| Text-heavy (prose, few tables) | pdftotext (poppler) | sudo apt install poppler-utils | ⚡ instant |
| Text-heavy fallback | pypdf | pip3 install pypdf | ⚡ instant |
| Text-heavy fallback | pdfminer.six | pip3 install pdfminer.six | ⚡ instant |
| Technical (code, tables, formulas) | docling | pip3 install docling | ~1.5s/page |
Before extraction begins, the skill asks you whether the book is technical or text-heavy and picks the right tool automatically. Docling preserves markdown tables and code blocks; pdftotext is faster for prose-only books.
Scanned PDFs need OCR first. A PDF that is page images with no text layer — a photographed or scanned book — has nothing for these tools to extract. The extractor checks the first pages and stops immediately with an explanation, rather than working through the whole book to produce an empty skill. Run OCR yourself, then convert the result:
ocrmypdf input.pdf output.pdf
EPUB:
| Tool | Install | Quality |
|---|---|---|
ebooklib + beautifulsoup4 | pip3 install ebooklib beautifulsoup4 | ⭐⭐⭐ Best |
stdlib zipfile | built-in — no install needed | ⭐⭐ Always available |
Other formats:
| Format | Tool | Install |
|---|---|---|
| DOCX | python-docx (fallback: stdlib ZIP/XML) | pip3 install python-docx |
| HTML | beautifulsoup4 (fallback: stdlib html.parser) | pip3 install beautifulsoup4 |
| RTF | striprtf (fallback: regex) | pip3 install striprtf |
| MOBI / AZW / AZW3 | Calibre ebook-convert (external app, not pip) | https://calibre-ebook.com/download |
| TXT / Markdown / reStructuredText / AsciiDoc | built-in | — |
📁 Repository structure
book-to-skill/
├── SKILL.md # Skill definition + step-by-step instructions (the generator spec)
├── scripts/
│ ├── extract.py # Thin entrypoint wrapper
│ └── extractor/ # Modular extraction package
│ ├── config.py # Extensions, paths, dependency constants
│ ├── dependencies.py # optional-dep probing + --check
│ ├── exceptions.py # ExtractionError (per-source failures, batch-safe)
│ ├── utils.py # CLI parsing, multi-source resolution, chapter detection, runner
│ └── parsers/ # Format-specific parsers (pdf, epub, docx, html, rtf, calibre, text)
├── tools/
│ ├── discovery_tax.py # measures token cost vs context-dump / discovery loop
│ └── validate_skill.py # checks a generated SKILL.md against host rules (--lens claude|copilot|amp|hermes|opencode)
├── tests/ # pytest suite (extraction, detection, discovery tax)
├── docs/
│ ├── performance.md # measured benchmarks, discovery tax, cost
│ └── architecture.md # pipeline + component map
├── CHANGELOG.md # release history (semver)
├── CONTRIBUTING.md # dev setup, PR conventions, release process
├── SECURITY.md # vulnerability reporting
└── README.md # This file
⚖️ Copyright & fair use
book-to-skill ships no book content — not a single page. It's a converter you point at files you already own.
- Processing is local. Extraction and analysis run on your machine. Your files are never uploaded by this tool. (If your agent's model runs in the cloud, the text you feed it follows that provider's normal data terms — same as any prompt.)
- You use your own copy. Bring a book you bought, docs your company owns, or papers you have the right to read.
- The output is your notes. A generated skill is a structured, synthesized derivative — framework names, definitions, takeaways — not a reproduction of the text. The skill explicitly never copies raw passages (see Quality Rule #7). Treat it like handwritten study notes: yours, for personal use.
- Don't redistribute. Publishing or sharing a generated skill of a copyrighted work can infringe the rights holder. Keep skills of third-party books private. Internal docs, your own writing, and openly-licensed material are fine to share within the bounds of their license.
When in doubt, follow the license or terms of the source document. This project is a tool; how you use it is on you.
💖 Sponsors
book-to-skill is free and MIT-licensed, maintained on personal time. If it saves you tokens or study hours, consider sponsoring its upkeep: PR reviews, multilingual fixes, releases, and docs.
Become a sponsor → github.com/sponsors/virgiliojr94
Every sponsor is listed in BACKERS.md. Thank you for keeping open, privacy-first tooling alive. ✨
License
MIT — applies to the converter (code + skill definition) in this repository, not to any book or document you process with it.
相關資源

Skill Seekers
CLI把文档站、GitHub 仓库、PDF、视频等 18 类来源整理成 Claude 等平台可用的技能包,也能导出为 RAG 分块与向量库数据;可选装 MCP 服务器,并能调用本地 Claude Code 等 agent 做内容增强。需要 Python 3.10+。
yusufkaraaslan/Skill_Seekers15.2k
evil-read-arxiv
Skill按研究兴趣每天从 arXiv 与 Semantic Scholar 推荐论文,精读后生成带插图的 Obsidian 笔记和论文关系图谱,也能检索 CVPR、NeurIPS 等顶会论文。需安装 Python 3 与 Obsidian,设置笔记库路径并填写研究兴趣配置;配套网页版另需 Anthropic API Key。
juliye2025/evil-read-arxiv1.7k
Tutor Skills
Skill两个配套技能:/tutor-setup 把 PDF、讲义或代码库整理成带概念笔记和练习题的 Obsidian 学习库,/tutor 再针对薄弱点出选择题测验并记录掌握程度;适合学生复习与自学,建议配合 Obsidian 查看。
bevibing/tutor-skills1.4k
dailypaper-skills
Skill说一句「今日论文推荐」,就从 HuggingFace Daily 和 arXiv 抓新论文,按研究方向打分筛选、生成推荐页,并把重点论文精读成 Obsidian 笔记,还能按 Zotero 分类批量阅读。需 Python 3、Obsidian 与 poppler,按 README 复制整个 skills 目录(含共享配置)安装。
huangkiki/dailypaper-skills1.3k
DeepPaperNote
Skill把一篇论文(标题、DOI、arXiv 号或本地 PDF)精读成结构化 Obsidian 笔记,保留研究问题、方法主线、关键公式、图表与局限,可优先读取本地 Zotero 条目,另附术语卡片技能。需 Python 3.10 以上并安装 PyMuPDF。
917Dhj/DeepPaperNote1.2k
learn-from-materials
Skill把书籍、PDF、PPT、Word、网页等资料转成可溯源的知识库和离线交互学习网页,含核心框架、术语表、方法论关系图、自测题和本地笔记,并区分资料原文与模型补充的内容;适合读书、备课和研读报告,需本机 Python 3.10+。
dmoshehun-prog/learn-from-materials1k