Book summarizer

v1.0.1

Use this skill when the user wants a long-form book summarized in the user's preferred language at an explicitly verified 20 percent compression ratio, with...

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byDaniel Lélis Baggio@dannyxyz22

Install

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for dannyxyz22/book-summarizer.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Book summarizer" (dannyxyz22/book-summarizer) from ClawHub.
Skill page: https://clawhub.ai/dannyxyz22/book-summarizer
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

CLI Commands

Use the direct CLI path if you want to install manually and keep every step visible.

OpenClaw CLI

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openclaw skills install book-summarizer

ClawHub CLI

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npx clawhub@latest install book-summarizer
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Purpose & Capability
Name/description match the included scripts and instructions. The three Python helper scripts implement counting, splitting, aggregating, and ratio verification which are appropriate for a summarizer. Minor mismatch: the skill declares no required binaries but the SKILL.md and scripts assume a Python runtime (commands like `python scripts/...`).
Instruction Scope
SKILL.md confines activity to local files and the provided scripts (count, split, aggregate, verify). It also instructs the agent to draft summary batches 'in chat' — which implies sending book text to the LLM provider during summarization. The skill itself does not add remote endpoints, but using it will typically transmit source text to whatever model/service the agent invokes.
Install Mechanism
No install spec (instruction-only). Scripts are bundled and rely only on the Python standard library; nothing is downloaded or executed from external URLs.
Credentials
No environment variables, credentials, or config paths are requested. The skill does not require unrelated secrets or system credentials.
Persistence & Privilege
always is false and the skill does not request elevated or persistent system presence. It does not modify other skills or system-wide settings.
Assessment
This package is internally consistent and only operates on local text files via bundled Python scripts. Before installing: (1) ensure you have a Python runtime available (the skill's metadata omits this dependency), (2) be aware that summarization normally involves sending book text to the model/provider — do not use it for sensitive/private documents unless you trust your model endpoint, and (3) respect copyright for non-public works. The code is small and uses only the standard library; review it yourself if you want to confirm behavior locally.

Like a lobster shell, security has layers — review code before you run it.

latestvk97c40fsg6r0p93089279g6fb1837j2r
184downloads
1stars
2versions
Updated 1mo ago
v1.0.1
MIT-0

Book Summarizer

Use this skill for requests like:

  • "Summarize this book at a 20% compression ratio"
  • "Generate a substantial summary and verify the ratio"
  • "Produce the summary in batches and validate the final total"

Rules

  • Default target ratio: 0.20
  • Default tolerance: 0.02
  • Accept only summaries between 18% and 22% of the original word count
  • Output must be in user's language of choice (e.g., pt-BR)
  • If the ratio is outside the allowed range, do not import the summary
  • In chat-only mode, if the source is very large, generate the summary in multiple batches and merge them before validation
  • All packaged helper scripts live in scripts/ inside this skill folder

Workflow

  1. Start from a local plain-text book file or a downloaded Project Gutenberg text.
  2. Count the source words with python scripts/book_tools.py count <original_file>.
  3. Compute the target summary length with python scripts/book_tools.py target <original_file> --ratio 0.20.
  4. If the source is too large for one reply, split it with python scripts/split_book.py <original_file> 3000.
  5. Draft summary batches in order, preserving chronology and section fidelity.
  6. Merge the batches with python scripts/book_tools.py aggregate <summary_file> <batch_files...>.
  7. Validate the final ratio with python scripts/verify_summary_ratio.py <original_file> <summary_file>.

Key Files

  • scripts/book_tools.py
  • scripts/split_book.py
  • scripts/verify_summary_ratio.py
  • SKILL.md

Notes

  • The packaged scripts use only the Python standard library.
  • Run the commands from the skill folder, or use explicit paths if you call them from elsewhere.
  • For very large books, prefer the automated pipeline over single-turn chat drafting.
  • In chat-only mode, books above roughly 80k words should be summarized over multiple turns; do not pretend a single short draft satisfies the 20% rule.

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