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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.

63

Quality

79%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./.github/plugins/azure-skills/skills/azure-ai/SKILL.md

The canonical home for this skill is azure-ai in microsoft/GitHub-Copilot-for-Azure

SKILL.md
Quality
Evals
Security

Quality

Content

67%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A lean, well-structured service catalog with concrete MCP commands, CLI alternatives, a setup fallback, and verified one-level-deep SDK references. The main weaknesses are concept-glossary tables that restate what Claude already knows and an auth best-practices file that is undiscoverable from the body.

Suggestions

Delete or collapse the 'AI Search Capabilities' and 'Speech Capabilities' tables — Claude already knows what full-text, vector, and hybrid search and speech-to-text are; keep only Azure-specific facts like limits or tool names.

Link references/auth-best-practices.md from the body (e.g., a one-line 'Authentication: see [auth-best-practices.md](references/auth-best-practices.md)' note) so that guidance is discoverable without going through the SDK files.

Add one short executable example in the body, such as an azure__search search_query invocation with typical arguments, so the most common operation is copy-paste ready without opening a reference file.

DimensionReasoningScore

Conciseness

Two full capability tables restate concepts Claude already knows ("Linguistic analysis, stemming", "Semantic similarity with embeddings", "Combined keyword + vector"), and MCP tool names appear in both the Services table and the MCP section. This matches 'mostly efficient but includes some unnecessary explanation or could be tightened'. It is above a 2 because the body is compact tables rather than padded prose, but below a 4 because the glossary tables and duplicated tool listings are clearly trimmable.

3 / 5

Actionability

Concrete, executable guidance is present: MCP tool/command pairs ("azure__search with command search_index_list"), CLI commands ("az search", "az cognitiveservices"), a setup fallback ("Run /azure:setup or enable via /mcp"), and working links to verified SDK reference files. This matches 'mostly executable guidance; concrete code or commands with minor gaps'. It is not a 5 because the body includes no actual usage example (e.g., a sample search_query invocation with arguments or parameters).

4 / 5

Workflow Clarity

Precedence is explicit ("MCP Server (Preferred)") and there is a clear conditional branch with a recovery path ("If Azure MCP is not enabled: Run /azure:setup or enable via /mcp"). This matches 'clear sequence with most checkpoints present; minor validation gaps'. It is not a 5 because no guidance sequences the MCP vs. CLI vs. SDK paths or what to do after setup, and not a 3 because there are no destructive or batch operations requiring validation and the lookup flow is unambiguous.

4 / 5

Progressive Disclosure

The body is a clean overview with well-sectioned, one-level-deep references, and all 14 linked SDK files exist in references/sdk/. This matches 'good structure; most content is appropriately placed; references mostly clear; minor organization gaps'. It is not a 5 because references/auth-best-practices.md is never linked from SKILL.md — it is only reachable through three of the SDK files — leaving that guidance buried, and the Service Details section adds little navigation beyond the SDK Quick References.

4 / 5

Total

15

/

20

Passed

Description

83%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A well-constructed description that explicitly states both what it does and when to use it, with strong natural-language trigger coverage and synonyms. The main gap is that two of the four named services (OpenAI and Document Intelligence) contribute no concrete actions or trigger terms beyond the service names themselves.

DimensionReasoningScore

Specificity

The description lists several concrete actions ("search, vector/hybrid search, speech-to-text, text-to-speech, transcription, OCR") across the four named services, matching the 'several specific actions; minor gaps' anchor. It falls short of a 5 because no actions are given for the OpenAI and Document Intelligence services it names (e.g., chat/completions, embeddings, DALL-E, form extraction), and it sits above a 3 because far more than 1-2 concrete actions are specified.

4 / 5

Completeness

It explicitly answers both questions with concrete trigger phrases: WHAT ("Helps with search, vector/hybrid search, speech-to-text, text-to-speech, transcription, OCR") and WHEN ("WHEN: AI Search, query search, vector search, hybrid search, semantic search, speech-to-text, text-to-speech, transcribe, OCR, convert text to speech"), matching the anchor for clearly and explicitly answering both. A 4 would require the when-clause to be only weakly explicit, which it is not.

5 / 5

Trigger Term Quality

The WHEN clause offers good natural-term coverage with synonyms ("speech-to-text"/"transcribe", "text-to-speech"/"convert text to speech", "vector search", "hybrid search", "semantic search", "OCR"), matching the 'good keyword coverage; a few natural terms missing' anchor. It is not a 5 because common phrasings such as "full-text search", "keyword search", "embeddings", "GPT/Azure OpenAI", and "form extraction" are absent, leaving a few natural triggers missing.

4 / 5

Distinctiveness Conflict Risk

The "Azure AI" framing plus service-specific terms ("AI Search", "Azure") carves a mostly distinct niche, matching the 'mostly distinct; minor overlap risk' anchor. It is not a 5 because generic trigger words like "search", "OCR", and "speech-to-text" could also match non-Azure search/OCR/speech skills; it is above a 3 because the Azure qualifier and named services keep the overlap minor.

4 / 5

Total

17

/

20

Passed

Validation

87%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

relative_links

Relative link issues: 14 deeper-than-1-level

Warning

referenced_paths_exist

Referenced path issues: 14 deeper-than-1-level

Warning

Total

14

/

16

Passed

Repository
microsoft/azure-skills
Reviewed

Table of Contents

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