Skills azure-ai-formrecognizer-java

📦

azure-ai-formrecognizer-java

Name: azure-ai-formrecognizer-java
Author: sickn33

Content revision r2 Safe ⚙️ External commands🌐 Network access

Build Java Document Intelligence Workflows

Java developers need reliable patterns for extracting structured data from documents. This skill provides Azure SDK examples for analysis, custom models, classification, and administration.

Supports: Claude Codex Code(CC)

🥉 78 Bronze

Install with my Agent

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Agent request

Review the Skillstore skill "azure-ai-formrecognizer-java" from https://skillstore.io/skills/sickn33-azure-ai-formrecognizer-java.md and its manifest at https://skillstore.io/api/skills/sickn33-azure-ai-formrecognizer-java/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

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Markdown detail GET /skills/sickn33-azure-ai-formrecognizer-java.md Signed manifest GET /api/skills/sickn33-azure-ai-formrecognizer-java/manifest Signed lockfile GET /api/skills/sickn33-azure-ai-formrecognizer-java/lockfile

Test it

Using "azure-ai-formrecognizer-java". Plan invoice extraction for a Java service that uses DefaultAzureCredential.

Expected outcome:

Recommended flow: add the Azure SDK dependencies, create the client with the service endpoint, submit invoices, poll results, and validate typed fields.

Using "azure-ai-formrecognizer-java". Explain how to train and inspect a custom invoice model.

Expected outcome:

Use a protected Azure Blob SAS URL and document prefix, start model training, wait for completion, then inspect model identifiers and field schemas.

Using "azure-ai-formrecognizer-java". Design classification for invoices and receipts.

Expected outcome:

Define separate Blob prefixes, build a classifier for both document types, classify each input, and route results using confidence-aware validation.

Security Audit

Safe

v5 • 7/23/2026 Open versioned report

All 38 external-command findings are false positives caused by Markdown fences or inline code in documentation; the file contains no shell execution. Both URL findings are benign placeholders for Azure SDK configuration and document analysis. No prompt injection, hidden execution, or exfiltration intent was found.

Files scanned

352

Lines analyzed

Review items

False positives ignored

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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Academic citations (APA · BibTeX · CFF)

APA citation

sickn33. (2026). azure-ai-formrecognizer-java security audit report (audit version 5) [Author version unspecified]. Skillstore. https://skillstore.io/skills/sickn33-azure-ai-formrecognizer-java/audits/5

BibTeX citation

@techreport{sickn33-sickn33-azure-ai-formrecognizer-java-2026,
  author = {sickn33},
  title = {azure-ai-formrecognizer-java security audit report (audit version 5)},
  institution = {Skillstore},
  year = {2026},
  number = {5},
  url = {https://skillstore.io/skills/sickn33-azure-ai-formrecognizer-java/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-formrecognizer-java 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-formrecognizer-java/audits/5"
identifiers:
  - type: other
    value: "skillstore:sickn33-azure-ai-formrecognizer-java:audit:5"
    description: "Skillstore immutable audit report identifier"

Skillstore Score

Why this score Evidence Confidence: High

Architecture

Maintainability

Content

Community

Spec Compliance

What You Can Build

Prototype invoice extraction

Create a Java workflow that sends invoices to a prebuilt model and safely reads common fields with confidence values.

Train custom document models

Plan model training from Azure Blob data, inspect field schemas, and analyze documents with the resulting model.

Operate a document model catalog

Compose, list, inspect, delete, and monitor custom models while checking Azure resource limits.

Try These Prompts

Configure a client

Show how to configure a Java DocumentAnalysisClient using DefaultAzureCredential for endpoint {endpoint}. Include the required Maven dependency and imports.

Extract invoice fields

Create a Java workflow that analyzes {document_url} with prebuilt-invoice. Extract common fields, confidence values, and handle missing fields.

Build a custom model

Design a Java workflow to build model {model_id} from Azure Blob SAS URL {sas_url}. Explain polling, prefixes, and result inspection.

Design classification architecture

Review an Azure Document Intelligence design for {document_types}. Propose classifier training, composed models, lifecycle operations, error handling, credential security, and validation.

Best Practices

Prefer DefaultAzureCredential and managed identity for deployed applications.
Validate field presence and DocumentField types before reading extracted values.
Apply confidence thresholds and protect sensitive document content according to Azure and organizational requirements.

Avoid

Do not hardcode API keys, production SAS URLs, or secrets in source code.
Do not assume every analyzed document contains all expected fields or field types.
Do not send untrusted document URLs without access controls, content validation, and cost safeguards.

Frequently Asked Questions

Which Java library does this skill cover?

It covers the Azure AI Form Recognizer document analysis SDK, now associated with Azure AI Document Intelligence.

Can it analyze local PDF files?

Yes. The examples load a local file as BinaryData and submit it to a prebuilt analysis model.

Does it support documents stored at URLs?

Yes. Several examples analyze remote documents by URL, subject to service access and source permissions.

Can it create custom extraction models?

Yes. It demonstrates building models from Azure Blob data, composing models, and inspecting model metadata.

Does it include document classification?

Yes. It shows classifier training for multiple document types and classification of a document URL.

Is the sample SDK version current for every project?

No. The documented dependency is 4.2.0-beta.1, so verify compatibility and current Azure guidance before implementation.

Developer Details

Author

sickn33

License

MIT

Skillstore revision

Version notice

The author did not declare a version.

Repository

https://github.com/sickn33/antigravity-awesome-skills/tree/main/skills/azure-ai-formrecognizer-java

Ref

f9e2c34b4f19c7f3e6b0a1e93227b5f77cc12526

Maintenance freshness

7/26/2026

Usage

7 downloads · 144 views

File structure

📄 SKILL.md

azure-ai-formrecognizer-java

Install with my Agent

Agent-readable resources

Test it

Security Audit

Risk Factors

Copy report link

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Embed card

APA citation

BibTeX citation

CITATION.cff

Skillstore Score

What You Can Build

Prototype invoice extraction

Train custom document models

Operate a document model catalog

Try These Prompts

Best Practices

Avoid

Frequently Asked Questions

Developer Details