Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Tyler-R-Kendrick/agent-skills --skill azure-aigit clone --depth 1 https://github.com/Tyler-R-Kendrick/agent-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/tyler-r-kendrick/agent-skills/azure-ai)<a href="https://agentmods.dev/skills/tyler-r-kendrick/agent-skills/azure-ai"><img src="https://agentmods.dev/badge/skills/tyler-r-kendrick/agent-skills/azure-ai/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/tyler-r-kendrick/agent-skills/azure-ai"><img src="https://agentmods.dev/badge/skills/tyler-r-kendrick/agent-skills/azure-ai.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00121 | $0.00728 |
| Opus 5.5 | $0.00048 | $0.00291 |
| Sonnet 5.5 | $0.00024 | $0.00146 |
| Haiku 4.5 | $0.00012 | $0.00073 |
Grade A, and why
azure-ai scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Azure AI Services
Services
| 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 |
- |
| Foundry | AI models, agents, prompt flows | azure__foundry |
az ml |
| OpenAI | GPT models, embeddings, DALL-E | - | az cognitiveservices |
| Document Intelligence | Form extraction, OCR | - | - |
MCP Server (Preferred)
When Azure MCP is enabled:
AI Search
azure__searchwith commandsearch_index_list- List search indexesazure__searchwith commandsearch_index_get- Get index detailsazure__searchwith commandsearch_query- Query search index
Speech
azure__speechwith commandspeech_transcribe- Speech to textazure__speechwith commandspeech_synthesize- Text to speech
Foundry
azure__foundrywith commandfoundry_model_list- List AI modelsazure__foundrywith commandfoundry_deployment_list- List deploymentsazure__foundrywith commandfoundry_agent_list- List AI agents
If Azure MCP is not enabled: Run /azure:setup or enable via /mcp.
AI Search Capabilities
| 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 |
Speech Capabilities
| 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 |
Foundry Capabilities
| Feature | Description |
|---|---|
| Model catalog | GPT-4, Llama, Mistral, custom |
| AI agents | Multi-turn, tool calling, RAG |
| Prompt flow | Orchestration, evaluation |
| Fine-tuning | Custom model training |
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2mo ago First seen · 72 lines · 121 tokens per session scan A 7ef7fd29aa9e
azure-ai is a skill published in the GitHub repository Tyler-R-Kendrick/agent-skills (13 stars, last pushed 5mo ago), licensed MIT. It adds 121 tokens to every session and 728 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
azure-ai compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| azure-aiTyler-R-Kendrick/agent-skills | Skill | 13 | 5mo ago | MIT | A | 121 | Claude Code |
| agent-platform-model-registrygoogle/skills | Skill | 22k | yesterday | Apache-2.0 | A | 60 | Claude Code, Codex |
| foundry-config-setupmicrosoft/agent-framework | Skill | 15k | yesterday | MIT | A | 65 | Claude Code, Codex |
| google-cloud-solution-agentic-analytics-spark-knowledge-cataloggoogle/skills | Skill | 22k | yesterday | Apache-2.0 | A | 132 | Claude Code, Codex |
| training-checkwanshuiyin/Auto-claude-code-research-in-sleep | Skill | 19k | 3d ago | MIT | A | 35 | Claude Code |
| nemo-automodel-launcher-configNVIDIA/skills | Skill | 3.9k | yesterday | Apache-2.0 | A | 30 | Claude Code |
| finetuningmicrosoft/skills | Skill | 3.2k | yesterday | MIT | A | 132 | Claude Code |