Agent skill

read-book

When you want to read and extract structured notes from a book — PDF, EPUB, MOBI, markdown, .txt, pasted text, or URL to a public-domain work. Reads in chunks (by chapter when a TOC exists, by 50-page blocks otherwise), extracts per-chapter TL;DR + key concepts + quotes + action items + frameworks, and offers to capture to second-brain raw/ as a highlights- file. Four modes — notes (default, chapter-by-chapter), summary (whole-book TL;DR + 3–5 takeaways), quotes (pull-quote highlights only), study (notes + Q&A spaced-rep prep). Triggers on "/read-book," "read this book," "extract notes from th

coreyhaines31github.com/coreyhaines31GitHub ↗
claude-codeMIT
Install
npx skills add coreyhaines31/makerskills --skill read-book --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 3
SKILL.md size: 8 KB
Bundled scripts: none
Version: 0.1.0
Path: skills/read-book/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 500

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# /read-book — Extract structured notes from books and long PDFs Sibling to `watch-video`. Same content-consumption pattern: ingest → chunk → extract → optionally capture to second-brain. ## Step 1 — Parse input Accept: - **PDF**: file path (Claude reads PDFs natively in chunks via `Read pages:"X-Y"`) - **EPUB / MOBI**: file path (needs `pandoc` or `ebook-convert` to extract — see `references/sources.md`) - **Markdown / .txt**: file path (read directly) - **Pasted text**: just use what was pasted - **URL** to public-domain text: `WebFetch` (Project Gutenberg, archive.org, etc.) Detect type from file extension. If ambiguous, ask. ## Step 2 — Parse mode | Invocation | Mode | What you get | |---|---|---| | `/read-book <input>` | **notes** (default) | Chapter-by-chapter: TL;DR + key concepts + quotes + action items + frameworks | | `/read-book <input> summary` | summary | Whole-book TL;DR (1 paragraph) + 3–5 key takeaways + who-it's-for | | `/read-book <input> quotes` | quotes | Pull-quote highlights only, with chapter context and page refs | | `/read-book <input> study` | study | Notes mode + 10–20 spaced-repetition Q&A cards | If the book is long (>200 pages) and mode is unspecified,

What's inside
Steps it walks through
  1. Step 1 — Parse input
  2. Step 2 — Parse mode
  3. Step 3 — Get the text + chunk
  4. Step 4 — Read each chunk
  5. Step 5 — Aggregate into final notes file
  6. Step 6 — Offer to capture to second-brain
  7. Step 7 — Report
  8. Modes (quick invocations)
  9. Composes with
  10. Error handling
  11. Notes on quality
Ships with 2 files
  • references/output-modes.md
  • references/sources.md
More from makerskills
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About this skill
What does the read-book skill do?

When you want to read and extract structured notes from a book — PDF, EPUB, MOBI, markdown, .txt, pasted text, or URL to a public-domain work. Reads in chunks (by chapter when a TOC exists, by 50-page blocks otherwise), extracts per-chapter TL;DR + key concepts + quotes + action items + frameworks, and offers to capture to second-brain raw/ as a highlights- file. Four modes — notes (default, chapter-by-chapter), summary (whole-book TL;DR + 3–5 takeaways), quotes (pull-quote highlights only), study (notes + Q&A spaced-rep prep). Triggers on "/read-book," "read this book," "extract notes from th

How do I install it?

Run `npx skills add coreyhaines31/makerskills --skill read-book --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From coreyhaines31/makerskills, a repository with 500 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going