gh-saharcarmel-sahar-claude-code-marketplace-plugins-candlekeep/skills/candlekeep

Candlekeep Skill

A personal knowledge base system that gives AI agents direct access to your books.

Quick Start

Installation

1. Install Python dependencies:

   cd plugins/candlekeep/skills/candlekeep
   uv sync
   

2. Initialize Candlekeep:

   uv run candlekeep init
   

   This creates ~/.candlekeep/ with database and configuration.

Usage

Add Books to Your Library

Add a PDF:

uv run candlekeep add-pdf ~/Documents/my-book.pdf \
  --title "Book Title" \
  --author "Author Name" \
  --tags "programming,reference"

Add a Markdown file:

uv run candlekeep add-markdown ~/Documents/notes.md \
  --title "My Notes" \
  --tags "documentation"

List Your Books

uv run candlekeep list

Output:

Books in library:
ID: 1
Title: The Pragmatic Programmer
Author: David Thomas, Andrew Hunt
Pages: 352
Format: pdf
Tags: programming, software-engineering

Query Your Library

Once books are added, simply ask Claude questions in natural language:

Example Questions:

• "Do I have any books on Python? Show me what they say about decorators"
• "What does my software architecture book say about microservices?"
• "List all books tagged with 'machine-learning'"

Claude will automatically:

1. List available books
2. Show table of contents
3. Extract relevant pages
4. Provide answers with page citations

Available Commands

All commands use uv run candlekeep from the skill directory.

init

Initialize the Candlekeep database and configuration.

add-pdf <file_path>

Add a PDF book to your library.

Options:

• --title - Book title (optional, extracted from metadata if not provided)
• --author - Author name (optional)
• --tags - Comma-separated tags (optional)

add-markdown <file_path>

Add a Markdown document to your library.

Options:

• --title - Document title (required)
• --author - Author name (optional)
• --tags - Comma-separated tags (optional)

list

List all books in your library with metadata.

toc <book_id>

Show the table of contents for a specific book.

uv run candlekeep toc 1

query <book_id> <start_page> <end_page>

Extract content from specific pages of a book.

uv run candlekeep query 1 10 15

Returns: Text content from pages 10-15 with page markers.

How It Works

Progressive Disclosure Pattern

Candlekeep uses a token-efficient approach:

1. Discovery - Lists book titles/metadata (~20-50 tokens per book)
2. Navigation - Shows table of contents when needed
3. Extraction - Fetches only requested page ranges
4. Citation - Includes page markers for precise references

This keeps context usage minimal while providing comprehensive access.

Privacy & Storage

• All data stored locally in ~/.candlekeep/candlekeep.db (SQLite)
• No external API calls - purely local processing
• Content stored as chunks with page-level granularity
• Efficient indexing by title, author, tags, and content

File Structure

~/.candlekeep/
├── candlekeep.db       # SQLite database
└── config.json         # Configuration

plugins/candlekeep/skills/candlekeep/
├── SKILL.md            # Skill definition for Claude
├── README.md           # This file
├── pyproject.toml      # Python dependencies
├── alembic/            # Database migrations
└── src/
    └── candlekeep/
        ├── cli.py              # Command-line interface
        ├── commands/           # Command implementations
        ├── db/                 # Database models
        ├── parsers/            # PDF/Markdown parsers
        └── utils/              # Utilities

Requirements

• Python: >=3.10
• UV: >=0.1.0 (package manager)

Troubleshooting

"Database not found"

Run uv run candlekeep init to initialize the database.

"PDF parsing failed"

Ensure the PDF is not corrupted and has extractable text. Some scanned PDFs without OCR won't work.

"Dependencies not installed"

Run uv sync from the skill directory to install all dependencies.

"Command not found: candlekeep"

Make sure you're running commands with uv run candlekeep prefix from the skill directory.

Tips for Great Results

1. Use descriptive tags - Makes it easier for Claude to find relevant books
2. Add complete metadata - Helps with discovery and citation
3. Break large documents - Consider splitting very large books into volumes
4. Regular queries - Reference books frequently to maximize value
5. Organize by topic - Use consistent tagging schemes

Support

For issues or questions:

• Review the Plugin README for installation help
• Check the SKILL.md for Claude's internal documentation
• Verify database exists at ~/.candlekeep/candlekeep.db

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Created by: Sahar Carmel
License: MIT