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Use Azure AI for search, speech, transcription, and OCR tasks.
The material indicates a prompt/documentation-style skill for Azure AI, with no declared keys, remote endpoints, local execution, or data/file access, so overall risk appears low. The main caveat is limited supply-chain clarity due to an undeclared license and sparse adoption/maintenance signals.
The material explicitly states that no keys or environment variables are required. There is no indication of requesting API keys, tokens, local credentials, or any credential storage/forwarding/reuse behavior.
The system flags it as prompt-only and lists no remote endpoint host. Although the description mentions Azure AI services such as Search, Speech, and OpenAI, it does not specify any endpoint this skill itself connects to or any implementation that automatically sends user data out.
There is no evidence of installation scripts, executable commands, local process spawning, or shell/CLI automation. References such as `az search` and `/azure:setup` in the README appear to be usage guidance rather than proof that the skill itself has code execution privileges.
The material does not declare access to local files, directories, clipboard, databases, or cloud credentials, nor does it describe write, delete, or bulk export capabilities. Based on the available facts, it does not indicate overbroad data access.
The source is an open-source Microsoft GitHub repository, which is a strong risk-reducing factor because it is auditable. However, the license is undeclared, community stars are 0, and maintenance status is unknown, so supply-chain maturity and ongoing maintenance signals are limited and should be verified before production use.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "azure-ai" skill from askskill: 1. Download https://raw.githubusercontent.com/microsoft/GitHub-Copilot-for-Azure/main/plugin/skills/azure-ai/SKILL.md 2. Save it as ~/.claude/skills/azure-ai/SKILL.md 3. Reload skills and tell me it's ready
Design an Azure AI Search vector search solution for product documentation, including index fields, embedding workflow, hybrid retrieval strategy, and one sample query.
A vector and hybrid search plan with index structure, workflow, and example query.
I have a customer service recording. Explain how to use Azure Speech to transcribe it into text and show an example output format with timestamps.
Steps, required settings, and a sample timestamped transcription output.
Use Azure Document Intelligence to process a scanned invoice, extract invoice number, date, amount, and vendor name, and present the result in JSON.
A field extraction approach and a structured JSON output example.
| Service | Use When | MCP Tools | CLI |
|---|---|---|---|
| AI Search | Full-text, vector, hybrid search | azure__search | az search |
| Speech | Speech-to-text, text-to-speech | azure__speech | - |
| OpenAI | GPT models, embeddings, DALL-E | - | az cognitiveservices |
| Document Intelligence | Form extraction, OCR | - | - |
When Azure MCP is enabled:
azure__search with command search_index_list - List search indexesazure__search with command search_index_get - Get index detailsazure__search with command search_query - Query search indexazure__speech with command speech_transcribe - Speech to textazure__speech with command speech_synthesize - Text to speechIf Azure MCP is not enabled: Run /azure:setup or enable via /mcp.
| Feature | Description |
|---|---|
| Full-text search | Linguistic analysis, stemming |
| Vector search | Semantic similarity with embeddings |
| Hybrid search | Combined keyword + vector |
| AI enrichment | Entity extraction, OCR, sentiment |
| Feature | Description |
|---|---|
| Speech-to-text | Real-time and batch transcription |
| Text-to-speech | Neural voices, SSML support |
| Speaker diarization | Identify who spoke when |
| Custom models | Domain-specific vocabulary |
For programmatic access to these services, see the condensed SDK guides:
For deep documentation on specific services:
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