How do I install the Azure Content Layout skill?

Run npx skillmds@latest add luokai0/azure-content-layout 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.

Is Azure Content Layout safe to use?

This skill has not completed SkillMD's automated safety review yet. Independent scanners report: SkillSpector: PASS, Skill Scanner: PASS. Capability flags: executes scripts, makes network calls. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Azure Content Layout?

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.

Is Azure Content Layout free to use?

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

Who published Azure Content Layout?

luokai0 (@luokai0) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Azure Content Layout by luokai0 — Agent Skill

Name: Azure Content Layout
Rating: 4.5 (4 reviews)
Author: luokai0

Azure Content Layout

Extract document structure, text, tables, and figures from documents using Azure Content Understanding prebuilt-layout analyzer. Converts PDF, images, Office docs into Markdown and structured JSON. Use when asked to extract text from documents, convert PDF/images to markdown, perform OCR, analyze document layout, or extract tables from files. Requires AZURE_CU_ENDPOINT and AZURE_CU_API_KEY environment variables.

luokai0 Updated Sep 8, 2026 10 repo stars

File contents

Azure Content Understanding — Layout Analyzer

Extract structured content from documents using Azure's prebuilt-layout analyzer. Outputs Markdown and structured JSON with text, tables, figures, and document hierarchy.

Setup

Set environment variables:

export AZURE_CU_ENDPOINT="https://YOUR_RESOURCE.services.ai.azure.com/"
export AZURE_CU_API_KEY="YOUR_KEY_HERE"

Optional: set API version (defaults to 2025-05-01-preview):

export AZURE_CU_API_VERSION="2025-11-01"

Quick Usage

Analyze a URL and print Markdown

node scripts/analyze.mjs --url "https://example.com/document.pdf"

Analyze a local file (pipe via stdin)

cat invoice.pdf | node scripts/analyze.mjs --stdin --markdown output.md --output result.json

Save both Markdown and full JSON

node scripts/analyze.mjs --url "https://example.com/report.pdf" \
  --markdown report.md \
  --output report.json

Direct API Call

When the script isn't available, use curl:

# Submit analysis (preview API)
curl -s -X POST "$AZURE_CU_ENDPOINT/contentunderstanding/analyzers/prebuilt-layout:analyze?api-version=2025-05-01-preview" \
  -H "Ocp-Apim-Subscription-Key: $AZURE_CU_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"url":"https://example.com/doc.pdf"}'

# Response includes Operation-Location header — poll that URL for results

For GA API (2025-11-01), the body format changes:

{"inputs": [{"url": "https://example.com/doc.pdf"}]}

Output

Markdown

The analyzer produces GitHub Flavored Markdown preserving:

Headings (h1–h6)
Tables (as HTML <table> blocks)
Selection marks (☒ checked, ☐ unchecked)
Figures (with references)
Paragraphs with reading order

Structured JSON

The full result includes detailed per-element data:

pages — dimensions, word/line counts per page
paragraphs — text blocks with bounding regions and semantic roles
tables — cells with row/column spans
figures — detected images/charts with bounding regions
sections — hierarchical document structure

Supported Formats

PDF, JPEG, PNG, BMP, TIFF, HEIF, DOCX, XLSX, PPTX, HTML

Best Practices

Async operation — the API returns 202; poll Operation-Location for results
Poll interval — 3 seconds is reasonable; results typically arrive in 5–60 seconds
Large documents — up to 2,000 pages supported; processing time scales linearly
File upload — use Content-Type: application/octet-stream with binary body
Tables — rendered as HTML in markdown for complex layouts (merged cells, etc.)

API Reference

See references/api.md for full request/response details.

---name: azure-content-layoutdescription: Extract document structure, text, tables, and figures from documents using Azure Content Understanding prebuilt-layout analyzer. Converts PDF, images, Office docs into Markdown and structured JSON. Use when asked to extract text from documents, convert PDF/images to markdown, perform OCR, analyze document layout, or extract tables from files. Requires AZURE_CU_ENDPOINT and AZURE_CU_API_KEY environment variables.---# Azure Content Understanding — Layout AnalyzerExtract structured content from documents using Azure's prebuilt-layout analyzer. Outputs Markdown and structured JSON with text, tables, figures, and document hierarchy.## SetupSet environment variables:```bashexport AZURE_CU_ENDPOINT="https://YOUR_RESOURCE.services.ai.azure.com/"export AZURE_CU_API_KEY="YOUR_KEY_HERE"```Optional: set API version (defaults to `2025-05-01-preview`):```bashexport AZURE_CU_API_VERSION="2025-11-01"```## Quick Usage### Analyze a URL and print Markdown```bashnode scripts/analyze.mjs --url "https://example.com/document.pdf"```### Analyze a local file (pipe via stdin)```bashcat invoice.pdf | node scripts/analyze.mjs --stdin --markdown output.md --output result.json```### Save both Markdown and full JSON```bashnode scripts/analyze.mjs --url "https://example.com/report.pdf" \ --markdown report.md \ --output report.json```## Direct API CallWhen the script isn't available, use curl:```bash# Submit analysis (preview API)curl -s -X POST "$AZURE_CU_ENDPOINT/contentunderstanding/analyzers/prebuilt-layout:analyze?api-version=2025-05-01-preview" \ -H "Ocp-Apim-Subscription-Key: $AZURE_CU_API_KEY" \ -H "Content-Type: application/json" \ -d '{"url":"https://example.com/doc.pdf"}'# Response includes Operation-Location header — poll that URL for results```For GA API (2025-11-01), the body format changes:```json{"inputs": [{"url": "https://example.com/doc.pdf"}]}```## Output### MarkdownThe analyzer produces GitHub Flavored Markdown preserving:- **Headings** (h1–h6)- **Tables** (as HTML `<table>` blocks)- **Selection marks** (☒ checked, ☐ unchecked)- **Figures** (with references)- **Paragraphs** with reading order### Structured JSONThe full result includes detailed per-element data:- `pages` — dimensions, word/line counts per page- `paragraphs` — text blocks with bounding regions and semantic roles- `tables` — cells with row/column spans- `figures` — detected images/charts with bounding regions- `sections` — hierarchical document structure## Supported FormatsPDF, JPEG, PNG, BMP, TIFF, HEIF, DOCX, XLSX, PPTX, HTML## Best Practices- **Async operation** — the API returns 202; poll `Operation-Location` for results- **Poll interval** — 3 seconds is reasonable; results typically arrive in 5–60 seconds- **Large documents** — up to 2,000 pages supported; processing time scales linearly- **File upload** — use `Content-Type: application/octet-stream` with binary body- **Tables** — rendered as HTML in markdown for complex layouts (merged cells, etc.)## API ReferenceSee [references/api.md](references/api.md) for full request/response details.

Frequently asked questions