azure-ai
Use for Azure AI: Search, Speech, OpenAI, Document Intelligence. Helps with search, vector/hybrid search, speech-to-text, text-to-speech, transcription, OCR. WHEN: AI Search, query search, vector search, hybrid search, semantic search, speech-to-text, text-to-speech, transcribe, OCR, convert text to speech.
85
77%
Does it follow best practices?
Impact
99%
2.02xAverage score across 3 eval scenarios
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./.github/plugins/azure-skills/skills/azure-ai/SKILL.mdQuality
Discovery
82%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This is a solid skill description that clearly identifies its Azure AI domain and provides explicit trigger terms via a 'WHEN:' clause. Its main strengths are comprehensive trigger term coverage and clear completeness with both what/when answered. Its weaknesses are that the capabilities listed are more like feature categories than concrete actions, and some trigger terms (OCR, search) are generic enough to potentially conflict with non-Azure skills.
Suggestions
Make capabilities more concrete by specifying actions like 'configure search indexes', 'transcribe audio files', 'extract text from scanned documents' rather than just listing feature areas.
Add Azure-specific qualifiers to generic terms to reduce conflict risk, e.g., 'Azure AI Search indexes' instead of just 'search', or 'Azure Document Intelligence OCR' instead of just 'OCR'.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description names the domain (Azure AI services) and lists several actions like search, speech-to-text, text-to-speech, transcription, and OCR, but these are more like feature areas than concrete specific actions (e.g., it doesn't say 'configure an Azure AI Search index' or 'transcribe audio files'). | 2 / 3 |
Completeness | The description clearly answers both 'what' (Azure AI services for search, speech, document intelligence) and 'when' with an explicit 'WHEN:' clause listing specific trigger scenarios. This satisfies the requirement for explicit trigger guidance. | 3 / 3 |
Trigger Term Quality | Excellent coverage of natural trigger terms users would say: 'vector search', 'hybrid search', 'semantic search', 'speech-to-text', 'text-to-speech', 'transcribe', 'OCR', 'AI Search'. These are terms users would naturally use when needing Azure AI capabilities. | 3 / 3 |
Distinctiveness Conflict Risk | While Azure-specific services provide some distinctiveness, terms like 'OCR', 'speech-to-text', and 'search' are quite generic and could overlap with non-Azure skills that handle similar tasks (e.g., a general OCR skill or a generic search skill). The Azure branding helps but doesn't fully eliminate conflict risk. | 2 / 3 |
Total | 10 / 12 Passed |
Implementation
72%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a well-organized reference skill that efficiently maps Azure AI services to their tools and capabilities. Its main strength is concise tabular presentation and excellent progressive disclosure to SDK references. Its weakness is the lack of executable code examples or concrete workflow sequences showing how to actually perform common tasks like querying a search index or transcribing audio.
Suggestions
Add at least one executable code snippet per major service (e.g., a complete MCP tool invocation for AI Search query with parameters, or a minimal SDK example for speech transcription).
Include a brief multi-step workflow for a common task like 'set up and query a vector search index' with explicit validation steps (e.g., verify index exists before querying).
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is lean and well-structured using tables to convey information efficiently. It avoids explaining what Azure services are or how they work conceptually, instead focusing on what tools to use and when. | 3 / 3 |
Actionability | The skill provides specific MCP tool commands and references to SDK guides, but lacks executable code examples. The MCP commands are named but don't show example invocations with parameters, and the SDK section only links to references without inline quick-start snippets. | 2 / 3 |
Workflow Clarity | The skill provides a clear decision table for which service to use and mentions the fallback path ('If Azure MCP is not enabled: Run /azure:setup'), but there are no multi-step workflows with validation checkpoints for common tasks like setting up a search index or running a transcription pipeline. | 2 / 3 |
Progressive Disclosure | Excellent progressive disclosure with a concise overview in the main file and well-organized, clearly signaled one-level-deep references to SDK guides across multiple languages and services, plus links to external Microsoft documentation for deep dives. | 3 / 3 |
Total | 10 / 12 Passed |
Validation
100%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 11 / 11 Passed
Validation for skill structure
No warnings or errors.
- Repository
- microsoft/azure-skills
- Commit
9d594ab
- Reviewed
Table of Contents
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