Habilidades azure-ai-document-intelligence-ts
📄

azure-ai-document-intelligence-ts

Seguro

Extract structured data from documents with Azure AI

Manually processing invoices, receipts, and forms is slow and error-prone. This skill automates document analysis using Azure Document Intelligence to extract text, tables, and fields with high accuracy.

Soporta: Claude Codex Code(CC)
📊 71 Adecuado
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Pruébalo

Usando "azure-ai-document-intelligence-ts". Analyze invoice from https://example.com/invoice-123.pdf

Resultado esperado:

Vendor: Contoso Electronics
Invoice Number: INV-2024-0892
Invoice Total: $1,247.50
Due Date: March 15, 2024
Confidence: 98.2%

Usando "azure-ai-document-intelligence-ts". Extract items from receipt image

Resultado esperado:

Merchant: Starbucks Store #4421
Date: Feb 20, 2024
Items:
- Caffee Latte (Large): $5.45
- Blueberry Muffin: $3.95
Subtotal: $9.40
Tax: $0.85
Total: $10.25

Auditoría de seguridad

Seguro
v1 • 2/24/2026

All static analysis findings are false positives. The detected 'backtick execution' patterns are markdown code block delimiters, not shell commands. Network URLs point to legitimate Azure endpoints. Environment variable access follows standard credential management practices. No malicious patterns detected.

1
Archivos escaneados
329
Líneas analizadas
0
hallazgos
1
Auditorías totales
No se encontraron problemas de seguridad
Auditado por: claude

Puntuación de calidad

38
Arquitectura
100
Mantenibilidad
87
Contenido
30
Comunidad
100
Seguridad
91
Cumplimiento de la especificación

Lo que puedes crear

Accounts Payable Automation

Automatically extract vendor name, invoice total, and due dates from supplier invoices for accounting workflows

Expense Report Processing

Parse receipt images to extract merchant, items, and totals for expense management systems

Identity Verification

Extract name, date of birth, and ID numbers from driver licenses and passports for KYC workflows

Prueba estos prompts

Basic Document Analysis 
Analyze this invoice PDF using Azure Document Intelligence. Extract the vendor name, invoice number, total amount, and due date. Return the results in a clear summary.
Receipt Item Extraction 
Process this receipt image and extract all line items with their descriptions and prices. Also extract the merchant name, transaction date, and total amount. List each item separately.
Batch Document Classification 
I have a folder of mixed documents (invoices, receipts, and contracts). Use a document classifier to identify each document type, then apply the appropriate prebuilt model to extract relevant fields from each. Summarize the results by document type.
Custom Form Processing 
Build a custom model to extract fields from our company's purchase order forms. The forms have fields for PO number, requester, department, line items with product codes and quantities, and approval signatures. Guide me through training data preparation and model deployment.

Mejores prácticas

  • Always use getLongRunningPoller() for document analysis since operations are asynchronous
  • Check confidence scores on extracted fields and set minimum thresholds for your use case
  • Use prebuilt models when available before investing in custom model training

Evitar

  • Do not skip error handling with isUnexpected() - always validate API responses
  • Avoid polling with manual loops - use the built-in poller for long-running operations
  • Do not hardcode credentials - use environment variables or Azure Key Vault for API keys

Preguntas frecuentes

What document formats are supported?
Azure Document Intelligence supports PDF, JPEG, PNG, BMP, TIFF, and HEIF formats. PDF is recommended for multi-page documents.
How long does document analysis take?
Analysis time varies by document complexity and page count. Simple documents take seconds, while complex multi-page documents may take several minutes. The skill handles polling automatically.
What is the difference between template and neural custom models?
Template models require documents with consistent layouts. Neural models handle layout variations and are recommended for most use cases, but require more training samples.
Can I process documents stored locally?
Yes, local files are supported by encoding them as base64 and sending in the request body. The skill demonstrates this pattern in the local file example.
How do I handle low-confidence field extractions?
Each extracted field includes a confidence score. Set a threshold (e.g., 0.8) and flag low-confidence results for human review before using in downstream processes.
What Azure region should I use?
Use the endpoint URL from your Azure Document Intelligence resource. Choose a region close to your users for lower latency and to meet data residency requirements.

Detalles del desarrollador

Autor

sickn33

Licencia

MIT

Repositorio

https://github.com/sickn33/antigravity-awesome-skills/tree/main/skills/azure-ai-document-intelligence-ts

Ref.

main

Estructura de archivos

📄 SKILL.md