OpenClaw

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.

chiefsegundo0 来源安装数☆ 0 仓库 Stars

查看来源 ↗安装与使用 SKILL.md ↗

安装与使用

请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求，再添加到工作流。

SkillHub CLI

skillhub install chiefsegundo/boof

打开来源仓库，查看说明和兼容环境后，按来源提供的命令或步骤安装。

将来源链接提供给你的 Agent，让它先读取说明、核对依赖，并向你说明将执行的安装步骤。

查看来源 ↗使用指南

技能说明

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.

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 Marker (local ML, no API) 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 (Marker + QMD).

Environment

MARKER_ENV — Path to marker-pdf Python venv (default: ~/.openclaw/tools/marker-env)
QMD_BIN — Path to qmd binary (default: ~/.bun/bin/qmd)
BOOF_OUTPUT_DIR — Default output director...

来源信息

Source: github
Repository: openclaw/skills
Path: skills/chiefsegundo/boof
Version: —
Commit: 97bf40bfe0d2e7c32ea1d4b40623ff6cdb152428
分类来源: rules
状态: active
可见性: public

这些信息来自收录时的来源分析，可能滞后；使用前请核对最新来源文件。

来源内容

SKILL.md

# 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.

## Quick Reference

### Convert + index a document
```bash
bash {SKILL_DIR}/scripts/boof.sh /path/to/document.pdf
```

### Convert with custom collection name
```bash
bash {SKILL_DIR}/scripts/boof.sh /path/to/document.pdf --collection my-project
```

### Query indexed content
```bash
qmd query "your question" -c collection-name
```

## Core Workflow

1. **Boof it:** Run `boof.sh` on a PDF. This converts it to markdown via Marker (local ML, no API) 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 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](references/setup-guide.md) for installation instructions (Marker + QMD).

## Environment

- `MARKER_ENV` — Path to marker-pdf Python venv (default: `~/.openclaw/tools/marker-env`)
- `QMD_BIN` — Path to qmd binary (default: `~/.bun/bin/qmd`)
- `BOOF_OUTPUT_DIR` — Default output director...

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