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Skills azure-ai-document-intelligence-ts
📦
azure-ai-document-intelligence-ts
Content revision r2 Safe ⚙️ External commands🌐 Network access🔑 Env variables
Build Azure Document Intelligence Workflows
Document extraction workflows require precise Azure REST SDK patterns and asynchronous operation handling. This skill provides practical TypeScript guidance for analysis, classification, and custom models.
Supports: Claude Codex Code(CC)
Install with my Agent
Copy this request to your Agent. It includes the canonical Skill page and manifest.
Agent request
Review the Skillstore skill "azure-ai-document-intelligence-ts" from https://skillstore.io/skills/sickn33-azure-ai-document-intelligence-ts.md and its manifest at https://skillstore.io/api/skills/sickn33-azure-ai-document-intelligence-ts/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.Your Agent should still show its plan and request any confirmation required by the security policy.
Agent-readable resources
Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.
Test it
Using "azure-ai-document-intelligence-ts". Analyze a local invoice and report the vendor, total, and due date.
Expected outcome:
- A TypeScript workflow reads and encodes the selected invoice.
- The prebuilt invoice model runs through an Azure long-running poller.
- The result handling reports vendor, total, and due date fields when available.
Using "azure-ai-document-intelligence-ts". Build a classifier for invoices and receipts stored in separate Azure Blob prefixes.
Expected outcome:
A classifier design maps each document type to its storage prefix, starts the build operation, checks errors, and reports the classifier identifier.
Using "azure-ai-document-intelligence-ts". List document models and show current custom model capacity.
Expected outcome:
A paginated model inventory is paired with the service limit and current custom model count.
Security Audit
Safev5 • 7/23/2026 Open versioned report
All 59 static alerts are false positives caused by Markdown syntax, placeholders, or standard environment-based configuration. The examples use official Azure packages and expose no credentials. No prompt injection, exfiltration intent, or other semantic threat was found.
1
Files scanned
334
Lines analyzed
0
Review items
0
False positives ignored
Risk Factors
⚙️ External commands (40)
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🌐 Network access (2)
No confirmed security findings were detected by the latest completed static and semantic audit. This does not prove the skill has no side effects.
Audited by: codex View Audit History →
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<iframe src="https://skillstore.io/embed/skills/sickn33-azure-ai-document-intelligence-ts.html" title="Skillstore Security Assessment" sandbox="allow-popups allow-popups-to-escape-sandbox" loading="lazy" referrerpolicy="no-referrer" width="420" height="180"></iframe>Academic citations (APA · BibTeX · CFF)
APA citation
sickn33. (2026). azure-ai-document-intelligence-ts security audit report (audit version 5) [Author version unspecified]. Skillstore. https://skillstore.io/skills/sickn33-azure-ai-document-intelligence-ts/audits/5BibTeX citation
@techreport{sickn33-sickn33-azure-ai-document-intelligence-ts-2026,
author = {sickn33},
title = {azure-ai-document-intelligence-ts security audit report (audit version 5)},
institution = {Skillstore},
year = {2026},
number = {5},
url = {https://skillstore.io/skills/sickn33-azure-ai-document-intelligence-ts/audits/5},
note = {Author version unspecified}
}CITATION.cff
cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "azure-ai-document-intelligence-ts security audit report (audit version 5)"
version: "unspecified"
type: report
authors:
- name: "sickn33"
date-released: "2026-07-23"
url: "https://skillstore.io/skills/sickn33-azure-ai-document-intelligence-ts/audits/5"
identifiers:
- type: other
value: "skillstore:sickn33-azure-ai-document-intelligence-ts:audit:5"
description: "Skillstore immutable audit report identifier"
Skillstore Score
Why this score Evidence Confidence: High 55
Architecture
85
Maintainability
87
Content
69
Community
83
Spec Compliance
What You Can Build
Automate Invoice Extraction
Create a TypeScript workflow that extracts vendor, total, due date, and line-item fields from invoices.
Classify Incoming Documents
Build and use a classifier that separates invoices, receipts, and other document types stored in Azure.
Train Specialized Models
Configure custom template or neural models from labeled documents in Azure Blob Storage.
Try These Prompts
Configure the Client
Show me how to install and configure the Azure Document Intelligence REST client in TypeScript using DefaultAzureCredential and an environment-based endpoint.
Analyze a Local Invoice
Create a TypeScript example that reads [file path], analyzes it with prebuilt-invoice, checks errors, polls completion, and reports key invoice fields.
Build a Document Classifier
Design a classifier for [document types] using training data under [Azure Blob prefixes]. Include environment configuration, polling, and result checks.
Design a Production Analysis Module
Design a typed TypeScript module for URL and local-file analysis using [model ID]. Include authentication choices, error handling, polling, pagination, and confidence thresholds.
Best Practices
- Prefer DefaultAzureCredential when managed identity or developer identity is available.
- Check isUnexpected before creating a poller, and handle failed long-running operations explicitly.
- Select the narrowest suitable model and enforce field confidence thresholds for the business workflow.
Avoid
- Do not hardcode API keys, SAS URLs, or resource-specific endpoints in source files.
- Do not send regulated or confidential documents without approved Azure privacy and residency controls.
- Do not assume extracted fields are correct when confidence values or required fields are missing.
Frequently Asked Questions
Which Azure package does this skill use?
It uses @azure-rest/ai-document-intelligence and optionally @azure/identity for DefaultAzureCredential.
Can it analyze local files?
Yes. The example reads a local file, converts it to base64, and sends it to Azure for analysis.
Does it support documents hosted at a URL?
Yes. Azure can analyze a document through a supplied URL when the service can access that location.
Which prebuilt models are covered?
The guidance covers read, layout, invoice, receipt, identity, tax, health insurance, contract, and bank statement models.
Can it create custom models and classifiers?
Yes. Examples use Azure Blob SAS URLs to build custom models and multi-type document classifiers.
Does the skill guarantee extraction accuracy?
No. Applications must evaluate confidence values, validate required fields, and add human review where errors have material impact.
Developer Details
Author
sickn33License
MIT
Skillstore revision
r2
Version notice
The author did not declare a version.
Ref
f9e2c34b4f19c7f3e6b0a1e93227b5f77cc12526
Maintenance freshness
7/26/2026
Usage
6 downloads · 157 views
File structure
📄 SKILL.md
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