Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
Version History
No file changes detected for version 1.0.1. No updates or modifications were made in this release.
What This Skill Does
A conversational interface for searching a personal book library using semantic embeddings. Ask questions in natural language and get back synthesized answers with page-level citations. Runs as a companion to the Librarian project via a three-layer architecture: AI skill, shell wrapper, and Python search engine.
Returns precise citations with page and paragraph numbers from local files instead of summarizing from memory or requiring a web search.
When to use it
- Finding what a specific author says about a topic across your library
- Locating passages in a single book by concept or keyword
- Getting cited answers from a topic folder of books
- Cross-referencing ideas across multiple texts without opening each file
- Querying a personal research archive by natural language
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: What does Graeber say about the origins of money?
- 1Load .library-index.json and .topic-index.json metadata
- 2Match query against known book titles and topic IDs to infer scope
- 3Build shell command: ./librarian.sh "origins of money" topic finance 5
- 4Parse JSON results from Python search engine
- 5Synthesize answer and format citations with page numbers
Paragraph summarizing Graeber's argument with inline citations like [Debt: The First 5000 Years, p.21, ¶2] and a sources list
Requirements
Accounts, API keys, or tools you or your AI assistant may need to set up while using this skill.