# Document Extraction

Use this skill for intelligent document processing and content extraction using...

- Repository: https://github.com/andrewyng/context-hub (13986 stars)
- Category: AI and agents
- License: MIT
- Last updated: 2026-05-31
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add andrewyng/context-hub --skill document-extraction -g -a claude-code -y`
Codex: `npx skills add andrewyng/context-hub --skill document-extraction -g -a codex -y`
Cursor: `npx skills add andrewyng/context-hub --skill document-extraction -g -a cursor -y`
Gemini CLI: `npx skills add andrewyng/context-hub --skill document-extraction -g -a gemini-cli -y`

## Description

Use this skill for intelligent document processing and content extraction using LandingAI's Agentic Document Extraction (ADE). Trigger when users need to (1) Parse documents (PDFs, images, spreadsheets, presentations) into structured Markdown with layout understanding, (2) Extract specific structured data from documents using schemas (invoice fields, form data, table data, etc.), (3) Classify and separate multi-document batches by type (invoices vs receipts, statements vs forms, etc.), (4) Process large documents asynchronously (up to 1GB/1000 pages), (5) Get visual grounding (bounding boxes, page numbers) for extracted content, use when users mention bounding boxes, word locations, grounding, highlighting extracted content, or showing where data appears in a document. Use this skill when the task involves understanding document content for a set of documents. In particular this skill can help you write code that run on sets of documents. This will increase speed, and reduce the cost of loading the documents on the Agent context window because you can use a single script to extract the information needed.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# Document Extraction (ADE)

## Overview

LandingAI's Agentic Document Extraction (ADE) is a document processing SaaS that parses, extracts, and classifies documents without requiring templates or training. It provides three main capabilities:

1. **Parse**: Convert documents into structured Markdown with hierarchical JSON representation
2. **Extract**: Pull specific structured data using JSON schemas or Pydantic models
3. **Split**: Classify and separate multi-document batches by type

**Key Benefits:**
- No ML training or templates required
- Layout-agnostic parsing (works with any document structure)
- Supports 20+ file formats (PDF, images, spreadsheets, presentations)
- Precise visual grounding (bounding boxes, page numbers)
- Multiple models optimized for different document types

## Quick Start

### 1. Installation

Never install packages globally without user approval. Always check for a local Python environment first.

```
1. .venv/bin/python, uv-managed (this project)
2. venv/bin/python, standard Python venv
3. uv run python, if pyproject.toml exists
4. poetry run python, if poetry.lock exists
5. python3, system fallback; warn the user
```
Use the local environment to install: `landingai-ade`, `python-dotenv`

### 2. API Key Setup

The user may have already setup a `.env` file in the same directory as the `document-extraction` skill with the API key. You MUST check this path first (ls -la .*/skills/document-extraction/.env). Also try checking on the same directory as this SKILL.md file.

If not, provide instructions to create one. The script below will search for `.env` in common locations and load it.

```bash
.venv/bin/python - << 'EOF'
import os
from pathlib import Path
from dotenv import load_dotenv

The rest: https://github.com/andrewyng/context-hub/blob/HEAD/content/landingai/skills/ade/document-extraction/SKILL.md