How do I install the Boof skill?

Run npx skillmds@latest add lord1egypt/boof in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

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Which AI agents work with Boof?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Lord1Egypt (@lord1egypt) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Boof by lord1egypt — Agent Skill

Name: Boof
Rating: 4.666666666666667 (3 reviews)
Author: Lord1Egypt

Boof

Convert PDFs and documents to markdown, index them locally for RAG retrieval, and analyze them token-efficiently. Use when asked to: read/analyze/summarize a PDF, process a document, boof a file, extract information from papers/decks/NOFOs, or when you need to work with large documents without filling the context window. Supports batch processing and cross-document queries.

Lord1Egypt Updated Sep 8, 2026 2 repo stars

File contents

Boof 🍑

Local-first document processing: PDF → markdown → RAG index → token-efficient analysis.

Documents stay local. Only relevant chunks go to the LLM. Maximum knowledge absorption, minimum token burn.

Powered by opendataloader-pdf — #1 in PDF parsing benchmarks (0.90 overall, 0.93 table accuracy). CPU-only, no GPU required.

Quick Reference

Convert + index a document

bash {SKILL_DIR}/scripts/boof.sh /path/to/document.pdf

Convert with custom collection name

bash {SKILL_DIR}/scripts/boof.sh /path/to/document.pdf --collection my-project

Query indexed content

qmd query "your question" -c collection-name

Core Workflow

Boof it: Run boof.sh on a PDF. This converts it to markdown via opendataloader-pdf (local Java engine, no API, no GPU) and indexes it into QMD for semantic search.
Query it: Use qmd query to retrieve only the relevant chunks. Send those chunks to the LLM — not the entire document.
Analyze it: The LLM sees focused, relevant excerpts. No wasted tokens, no lost-in-the-middle problems.

When to Use Each Approach

"Analyze this specific aspect of the paper" → Boof + query (cheapest, most focused)

"Summarize this entire document" → Boof, then read the markdown section by section. Summarize each section individually, then merge summaries. See advanced-usage.md.

"Compare findings across multiple papers" → Boof all papers into one collection, then query across them.

"Find where the paper discusses X" → qmd search "X" -c collection for exact match, qmd query "X" -c collection for semantic match.

Output Location

Converted markdown files are saved to knowledge/boofed/ by default (override with --output-dir).

Setup

If boof.sh reports missing dependencies, see setup-guide.md for installation instructions (Java + opendataloader-pdf + QMD).

Environment

ODL_ENV — Path to opendataloader-pdf Python venv (default: ~/.openclaw/tools/odl-env)
QMD_BIN — Path to qmd binary (default: ~/.bun/bin/qmd)
BOOF_OUTPUT_DIR — Default output directory (default: ~/.openclaw/workspace/knowledge/boofed)

---name: boofdescription: Convert PDFs and documents to markdown, index them locally for RAG retrieval, and analyze them token-efficiently. Use when asked to: read/analyze/summarize a PDF, process a document, boof a file, extract information from papers/decks/NOFOs, or when you need to work with large documents without filling the context window. Supports batch processing and cross-document queries.---# Boof 🍑Local-first document processing: PDF → markdown → RAG index → token-efficient analysis.Documents stay local. Only relevant chunks go to the LLM. Maximum knowledge absorption, minimum token burn.Powered by [opendataloader-pdf](https://github.com/opendataloader-project/opendataloader-pdf) — #1 in PDF parsing benchmarks (0.90 overall, 0.93 table accuracy). CPU-only, no GPU required.## Quick Reference### Convert + index a document```bashbash {SKILL_DIR}/scripts/boof.sh /path/to/document.pdf```### Convert with custom collection name```bashbash {SKILL_DIR}/scripts/boof.sh /path/to/document.pdf --collection my-project```### Query indexed content```bashqmd query "your question" -c collection-name```## Core Workflow1. **Boof it:** Run `boof.sh` on a PDF. This converts it to markdown via opendataloader-pdf (local Java engine, no API, no GPU) and indexes it into QMD for semantic search.2. **Query it:** Use `qmd query` to retrieve only the relevant chunks. Send those chunks to the LLM — not the entire document.3. **Analyze it:** The LLM sees focused, relevant excerpts. No wasted tokens, no lost-in-the-middle problems.## When to Use Each Approach**"Analyze this specific aspect of the paper"** → Boof + query (cheapest, most focused)**"Summarize this entire document"** → Boof, then read the markdown section by section. Summarize each section individually, then merge summaries. See [advanced-usage.md](references/advanced-usage.md).**"Compare findings across multiple papers"** → Boof all papers into one collection, then query across them.**"Find where the paper discusses X"** → `qmd search "X" -c collection` for exact match, `qmd query "X" -c collection` for semantic match.## Output LocationConverted markdown files are saved to `knowledge/boofed/` by default (override with `--output-dir`).## SetupIf `boof.sh` reports missing dependencies, see [setup-guide.md](references/setup-guide.md) for installation instructions (Java + opendataloader-pdf + QMD).## Environment- `ODL_ENV` — Path to opendataloader-pdf Python venv (default: `~/.openclaw/tools/odl-env`)- `QMD_BIN` — Path to qmd binary (default: `~/.bun/bin/qmd`)- `BOOF_OUTPUT_DIR` — Default output directory (default: `~/.openclaw/workspace/knowledge/boofed`)

Frequently asked questions