skills.rest
nrl-ai
nrl-aiOFFICIAL
Explore all skills by this author →
WebsiteGitHub

document-workflows

Automate document processing pipelines with LandingAI ADE for parsing, extraction, and RAG preparation.

11|2|Updated Mar 21, 2026
Search Tags:#rag#visualization#grounding#chunking#snowflake#document-workflows#ade
One-click install
npx skills add https://github.com/nrl-ai/chub --skill document-workflows-nrl-ai
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: document-workflows
Source: https://github.com/nrl-ai/chub/tree/main/content/landingai/skills/ade/document-workflows
Command: npx skills add https://github.com/nrl-ai/chub --skill document-workflows-nrl-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Document workflows are often custom-built, brittle, and time-consuming to stitch together. This skill provides a coherent, end-to-end framework for parsing, classifying, extracting, and visualizing results from diverse documents using LandingAI ADE, reducing manual integration work and enabling repeatable pipelines.

Core Features & Use Cases

  • End-to-end pipelines: parse, extract, classify, and optionally split multi-page documents into coherent workflows.
  • RAG prep and visualization: chunking, grounding overlays, and UI-ready outputs for retrieval, QA, and dashboards.
  • Database-ready outputs: flattening results for CSV, DataFrame, and Snowflake ingestion, with optional streaming or UI layers.

Quick Start

Provide a folder of documents and run the ADE workflow to parse, classify, extract, and visualize results.

Frequently Asked Questions about document-workflows

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate end-to-end document processing pipelines for batch extraction?▼

Automate end-to-end document processing pipelines by providing a folder of documents to the ADE workflow, which parses, classifies, extracts, and visualizes results for batch processing. This reduces manual integration work and enables repeatable pipelines.

What is the best way to prepare diverse documents for RAG with chunking and grounding?▼

Preparing diverse documents for RAG involves using the ADE workflow to apply chunking and grounding overlays, generating UI-ready outputs for retrieval, QA, and dashboards. This provides a coherent framework for RAG preparation and visualization.

Can I export extracted document data to Snowflake or CSV?▼

You can export extracted document data to Snowflake or CSV by flattening results for database ingestion. The workflow supports database-ready outputs, allowing optional integration with Snowflake or standard CSV exports.

Does the ADE workflow support multi-type document classification and extraction?▼

The ADE workflow supports multi-type document classification and extraction, handling diverse documents within a single coherent flow. It applies to batch processing and optional split workflows for multi-page documents.

How do I visualize extraction results and review parsed documents?▼

Visualize extraction results and review parsed documents using the built-in visualization and UI layer. The workflow generates grounding overlays and UI-ready outputs for review, retrieval, and dashboards.

Related Skills

Explore More Software Engineering Skills→
ClyptAIClyptAI

document-extraction

Parse and extract structured data from PDFs, images, and spreadsheets using LandingAI ADE.

Official
Advanced
sfc-gh-miwhitakersfc-gh-miwhitaker
3

ap-invoice

Automate AP invoice processing in Snowflake with PDF extraction and GL classification.

Community
Advanced
0xHoneyJar0xHoneyJar
2

validating

Validate UI sprint components' physics and rigor compliance via Markdown reports.

Official
Intermediate
RambleRainbowRambleRainbow

regex-vs-llm-structured-text

Select between regex and LLM parsing for structured text with confidence scoring.

Community
Advanced