azure-ai-formrecognizer-java
Build document analysis applications using the Azure AI Document Intelligence SDK for Java.
57
48%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Advisory
Suggest reviewing before use
Optimize this skill with Tessl
npx tessl skill review --optimize ./skills/antigravity-azure-ai-formrecognizer-java/SKILL.mdQuality
Discovery
40%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
The description identifies a clear and specific technology niche (Azure AI Document Intelligence SDK for Java) which makes it distinctive, but it lacks concrete action verbs describing what the skill enables and completely omits trigger guidance for when Claude should select it. Adding specific capabilities and a 'Use when...' clause would significantly improve its effectiveness for skill selection.
Suggestions
Add a 'Use when...' clause with trigger terms like 'Use when the user needs to build Java applications that analyze documents, extract text, recognize forms, or process receipts/invoices using Azure AI Document Intelligence (formerly Form Recognizer).'
List specific concrete actions the skill covers, such as 'extract text, tables, and key-value pairs from documents, analyze custom/prebuilt models, process receipts, invoices, and ID documents'.
Include common alternative terms users might use, such as 'Form Recognizer', 'OCR', 'Azure cognitive services', and specific document types like 'receipts', 'invoices', 'ID documents'.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (document analysis applications) and the technology (Azure AI Document Intelligence SDK for Java), but doesn't list specific concrete actions like extracting tables, recognizing forms, processing receipts, etc. | 2 / 3 |
Completeness | Describes what (build document analysis applications using Azure AI Document Intelligence SDK for Java) but completely lacks a 'Use when...' clause or any explicit trigger guidance for when Claude should select this skill. Per rubric guidelines, missing 'Use when' caps completeness at 2, and the 'what' is also not very detailed, warranting a 1. | 1 / 3 |
Trigger Term Quality | Includes relevant keywords like 'Azure AI Document Intelligence', 'SDK', 'Java', and 'document analysis', but misses common variations users might say such as 'Form Recognizer' (the previous name), 'OCR', 'extract text', 'PDF analysis', or specific document types. | 2 / 3 |
Distinctiveness Conflict Risk | The combination of 'Azure AI Document Intelligence SDK' and 'Java' creates a very specific niche that is unlikely to conflict with other skills. This is a clearly distinct technology and language combination. | 3 / 3 |
Total | 8 / 12 Passed |
Implementation
57%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The skill provides highly actionable, executable Java code examples covering the full breadth of the Azure Document Intelligence SDK. However, it suffers from being a monolithic reference document rather than a well-structured skill overview with progressive disclosure. It lacks workflow validation steps for multi-step operations like custom model building and could be significantly more concise by splitting detailed examples into separate files.
Suggestions
Split detailed sections (Custom Models, Document Classification, Manage Models) into separate reference files and link to them from a concise SKILL.md overview
Add validation checkpoints to the custom model workflow: verify training data format, check model accuracy metrics after build, test with sample documents before production use
Remove boilerplate sections ('Trigger Phrases', 'When to Use', 'Limitations') that don't add actionable value for Claude
Condense the SKILL.md to a quick-start pattern (client creation + one core example) with clear navigation to detailed reference files
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is mostly efficient with executable code examples, but it's quite long (~300 lines) and includes some sections that could be condensed or split into separate reference files. The prebuilt models table and extensive code examples for every use case make it verbose for a SKILL.md overview. The 'Trigger Phrases', 'When to Use', and 'Limitations' sections at the end are boilerplate that add little value. | 2 / 3 |
Actionability | All code examples are fully executable Java with proper imports, concrete method calls, and realistic patterns. The examples cover client creation, layout extraction, receipt analysis, custom model building, classification, and error handling — all copy-paste ready with clear placeholders. | 3 / 3 |
Workflow Clarity | While individual operations are clear, multi-step workflows like building custom models (prepare training data → build → validate → use) lack explicit validation checkpoints and error recovery loops. The custom model building section doesn't mention verifying training data format or checking model accuracy before deployment. | 2 / 3 |
Progressive Disclosure | This is a monolithic wall of content with no references to external files. All detailed API patterns, custom model management, classification, and error handling are inlined. This would benefit greatly from splitting into separate reference files (e.g., CUSTOM_MODELS.md, CLASSIFICATION.md) with the SKILL.md serving as a concise overview. | 1 / 3 |
Total | 8 / 12 Passed |
Validation
90%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 10 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 10 / 11 Passed | |
- Repository
- boisenoise/skills-collections
- Commit
431bfad
- Reviewed
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