Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub Β· AI
Azure Document OCR
Extract text and structured data from documents using Azure Document Intelligence (formerly Form Recognizer). Supports OCR for PDFs, images, scanned document...
skill openclawclawhub Free
Extract text and structured data from documents using Azure Document Intelligence (formerly Form Recognizer). Supports OCR for PDFs, images, scanned document...
β¬ 0 downloads β
0 stars Unverified but indexed
Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.md, references/models.md, scripts/batch_ocr.py, scripts/ocr_extract.py
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.0
Provenance
- Publisher
- Li-Hongmin
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
Azure Document Intelligence OCR
Extract text and structured data from documents using Azure Document Intelligence REST API.
1. Environment Setup
Set your Azure Document Intelligence credentials: export AZURE_DOC_INTEL_ENDPOINT="https://your-resource.cognitiveservices.azure.com" export AZURE_DOC_INTEL_KEY="your-api-key"
2. Single File OCR
# Basic text extraction from PDF python scripts/ocr_extract.py document.pdf # Extract with layout (tables, structure) python scripts/ocr_extract.py document.pdf --model prebuilt-layout --format markdown # Process invoice python scripts/ocr_extract.py invoice.pdf --model prebuilt-invoice --format json # OCR from URL python scripts/ocr_extract.py --url "https://example.com/document.pdf" # Save output to file python scripts/ocr_extract.py document.pdf --output result.txt # Extract specific pages python scripts/ocr_extract.py document.pdf --pages 1-3,5
3. Batch Processing
# Process all documents in a folder python scripts/batch_ocr.py ./documents/ # Custom output directory and format python scripts/batch_ocr.py ./documents/ --output-dir ./extracted/ --format markdown # Use layout model with 8 workers python scripts/batch_ocr.py ./documents/ --model prebuilt-layout --workers 8 # Filter specific extensions python scripts/batch_ocr.py ./documents/ --ext .pdf,.png
Model Selection Guide
Document TypeRecommended ModelUse CaseGeneral textprebuilt-readPure text extraction, any documentStructured docsprebuilt-layoutTables, forms, paragraphs, figuresInvoicesprebuilt-invoiceVendor info, line items, totalsReceiptsprebuilt-receiptMerchant, items, totals, datesIDs/Passportsprebuilt-idDocumentIdentity documentsBusiness cardsprebuilt-businessCardContact informationW-2 formsprebuilt-tax.us.w2US tax documentsInsurance cardsprebuilt-healthInsuranceCard.usHealth insurance info See references/models.md for detailed model documentation.
Supported Input Formats
PDF: .pdf (including scanned PDFs) Images: .png, .jpg, .jpeg, .tiff, .bmp URLs: Direct links to documents
Output Formats
text: Plain text concatenation of all extracted content markdown: Structured output with headers and tables (best with layout model) json: Raw API response with full extraction details
Features
Handwriting Recognition: Extracts handwritten text alongside printed text CJK Support: Full support for Chinese, Japanese, Korean characters Table Extraction: Preserves table structure (use layout model) Multi-page Processing: Handles documents with multiple pages Concurrent Processing: Batch script supports parallel processing URL Input: Process documents directly from URLs
Environment Variables
VariableRequiredDescriptionAZURE_DOC_INTEL_ENDPOINTYesAzure Document Intelligence endpoint URLAZURE_DOC_INTEL_KEYYesAPI subscription key
Error Handling
Invalid credentials: Check endpoint URL and API key Unsupported format: Ensure file extension matches supported types Timeout: Large documents may need longer processing (max 300s) Rate limiting: Reduce concurrent workers for batch processing
Extract text from scanned PDF
python scripts/ocr_extract.py scanned_contract.pdf --model prebuilt-read
Process invoices with structured output
python scripts/ocr_extract.py invoice.pdf --model prebuilt-invoice --format json --output invoice_data.json
Batch process with layout analysis
python scripts/batch_ocr.py ./reports/ --model prebuilt-layout --format markdown --workers 4
Extract specific pages from large document
python scripts/ocr_extract.py large_doc.pdf --pages 1,3-5,10 --format text
Category context
Agent frameworks, memory systems, reasoning layers, and model-native orchestration.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
2 Docs2 Scripts
- SKILL.md
- references/models.md
- scripts/batch_ocr.py
- scripts/ocr_extract.py