azure-ai-document-intelligence-dotnet
Azure AI Document Intelligence SDK for .NET. Extract text, tables, and structured data from documents using prebuilt and custom models.
69
62%
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-document-intelligence-dotnet/SKILL.mdQuality
Discovery
67%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 is strong in specificity and distinctiveness, clearly identifying the Azure AI Document Intelligence SDK for .NET and listing concrete extraction capabilities. However, it lacks an explicit 'Use when...' clause and could benefit from additional natural trigger terms that users commonly use (e.g., 'OCR', 'Form Recognizer', 'C#').
Suggestions
Add an explicit 'Use when...' clause, e.g., 'Use when the user needs to extract data from documents using Azure AI Document Intelligence, Form Recognizer, or OCR in a .NET/C# project.'
Include common trigger term variations such as 'OCR', 'Form Recognizer' (the former product name), 'C#', 'invoice', 'receipt', and specific file types like '.pdf', '.tiff', '.jpeg'.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'Extract text, tables, and structured data from documents' and specifies the technology stack ('Azure AI Document Intelligence SDK for .NET') and model types ('prebuilt and custom models'). | 3 / 3 |
Completeness | Clearly answers 'what does this do' (extract text, tables, structured data using Azure AI Document Intelligence SDK for .NET), but lacks an explicit 'Use when...' clause or equivalent trigger guidance, which caps this at 2 per the rubric. | 2 / 3 |
Trigger Term Quality | Includes relevant keywords like 'Azure AI Document Intelligence', 'SDK', '.NET', 'extract text', 'tables', 'structured data', and 'documents', but misses common user variations like 'OCR', 'form recognizer', 'C#', '.pdf', 'invoice extraction', or 'receipt scanning'. | 2 / 3 |
Distinctiveness Conflict Risk | The combination of 'Azure AI Document Intelligence SDK' and '.NET' creates a very specific niche that is unlikely to conflict with generic document processing skills or other cloud provider SDKs. | 3 / 3 |
Total | 10 / 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.
This is a thorough and highly actionable SDK reference with excellent executable code examples covering all major operations. However, it suffers from being a monolithic document (~300 lines) that would benefit from progressive disclosure via separate reference files, and its workflows lack explicit validation checkpoints and error recovery patterns that would be important for production use.
Suggestions
Split detailed workflow examples and type references into separate files (e.g., WORKFLOWS.md, REFERENCE.md) and link from the main SKILL.md overview
Add validation checkpoints to workflows, especially for custom model building (e.g., verify training data format, check model status, validate extraction results against expected fields)
Remove the generic boilerplate 'When to Use' and 'Limitations' sections that don't add SDK-specific value
Integrate error handling into the workflow examples rather than having a separate section, showing how to handle and recover from failures at each step
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is fairly comprehensive but includes some unnecessary content like the 'When to Use' and 'Limitations' boilerplate sections that add no value, and the reference tables (prebuilt models, key types, related SDKs) could be more tightly organized or offloaded. The code examples themselves are reasonably lean but the overall document is quite long for a SKILL.md. | 2 / 3 |
Actionability | All code examples are fully executable C# with proper using statements, concrete API calls, and realistic field extraction patterns. The examples cover the full range of operations (analyze, build, classify, manage) with copy-paste ready code. | 3 / 3 |
Workflow Clarity | The workflows are presented as numbered sections with clear code, but they lack validation checkpoints and error recovery feedback loops. For example, the 'Build Custom Model' workflow doesn't mention validating training data or handling build failures, and the general error handling section is separate rather than integrated into workflows. | 2 / 3 |
Progressive Disclosure | The entire skill is a monolithic document with no references to separate files for detailed content. The prebuilt models table, key types reference, and 7 full workflow examples are all inline, making this a very long single file that would benefit from splitting into overview + detailed reference files. | 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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