virgiliojr94/book-to-skill

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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:

1. Point it at a file, folder, or glob — /book-to-skill ./my-book.pdf
2. It distills the book into a skill — frameworks, decision rules, anti-patterns, and per-chapter files. Structure, not a summary.
3. Your agent loads it on demand — ask /my-book replication and it reads the right chapter and answers from the real content, no hallucination.

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.

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:

Chapter files are loaded on-demand — they don't count against the skill budget until you ask about that topic.

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.

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

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

/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.

# 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

Common questions — "why not just dump the PDF?", cost, privacy, non-book inputs, multi-file books.

❓ Answers → docs/faq.md

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

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.

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. ✨

MIT — applies to the converter (code + skill definition) in this repository, not to any book or document you process with it.