Expert knowledge for Microsoft Foundry Local (aka Azure AI Foundry Local) development including best practices, configuration, and integrations & coding patterns. Use when compiling HF models with Olive, using Foundry Local CLI, chat/embeddings APIs, transcription, or tool calling, and other Microsoft Foundry Local related development tasks. Not for Microsoft Foundry (use microsoft-foundry), Microsoft Foundry Classic (use microsoft-foundry-classic), Microsoft Foundry Tools (use microsoft-foundry-tools), Azure Local (use azure-local).
npx skills add https://github.com/MicrosoftDocs/Agent-Skills --skill microsoft-foundry-local
This skill provides expert guidance for Microsoft Foundry Local. Covers best practices, configuration, and integrations & coding patterns. It combines local quick-reference content with remote documentation fetching capabilities.
> IMPORTANT for Agent: Use the Category Index below to locate relevant sections. For categories with line ranges (e.g., L35-L120), use read_file with the specified lines. For categories with file links (e.g., security.md), use read_file on the linked reference file
> IMPORTANT for Agent: If metadata.generated_at is more than 3 months old, suggest the user pull the latest version from the repository. If mcp_microsoftdocs tools are not available, suggest the user install it: Installation Guide
This skill requires network access to fetch documentation content:
mcp_microsoftdocs:microsoft_docs_fetch with query string from=learn-agent-skill. Returns Markdown.fetch_webpage with query string from=learn-agent-skill&accept=text/markdown. Returns Markdown.| Category | Lines | Description |
|----------|-------|-------------|
| Best Practices | L31-L35 | Guidance on using Foundry Local CLI effectively, following recommended workflows, and diagnosing/fixing common CLI issues and misconfigurations. |
| Configuration | L36-L43 | Compiling Hugging Face models with Olive, installing/configuring the Foundry Local CLI, managing local models, and migrating apps to the new Foundry Local SDK. |
| Integrations & Coding Patterns | L44-L56 | Using Foundry Local APIs/SDKs for chat, embeddings, transcription, OpenAI-compatible clients, LangChain apps, tool calling, and REST/SDK reference (C#, JS, Python, Rust, legacy). |
| Topic | URL |
|-------|-----|
| Apply best practices and fix issues in Foundry Local CLI | https://learn.microsoft.com/en-us/azure/foundry-local/reference/reference-best-practice |
| Topic | URL |
|-------|-----|
| Compile Hugging Face models for Foundry Local with Olive | https://learn.microsoft.com/en-us/azure/foundry-local/how-to/how-to-compile-hugging-face-models |
| Use Foundry Local CLI to manage local models | https://learn.microsoft.com/en-us/azure/foundry-local/how-to/how-to-use-foundry-local-cli |
| Use and configure Foundry Local CLI commands | https://learn.microsoft.com/en-us/azure/foundry-local/reference/reference-cli |
| Migrate and reconfigure apps to new Foundry Local SDK | https://learn.microsoft.com/en-us/azure/foundry-local/reference/reference-sdk-migration |
| Topic | URL |
|-------|-----|
| Generate text embeddings with Foundry Local SDK | https://learn.microsoft.com/en-us/azure/foundry-local/how-to/how-to-generate-embeddings |
| Integrate Foundry Local with OpenAI-style inference SDKs | https://learn.microsoft.com/en-us/azure/foundry-local/how-to/how-to-integrate-with-inference-sdks |
| Live microphone transcription with Foundry Local | https://learn.microsoft.com/en-us/azure/foundry-local/how-to/how-to-live-transcribe-audio |
| Transcribe audio using Foundry Local transcription API | https://learn.microsoft.com/en-us/azure/foundry-local/how-to/how-to-transcribe-audio |
| Build a LangChain translation app with Foundry Local | https://learn.microsoft.com/en-us/azure/foundry-local/how-to/how-to-use-langchain-with-foundry-local |
| Use Foundry Local native chat completions API | https://learn.microsoft.com/en-us/azure/foundry-local/how-to/how-to-use-native-chat-completions |
| Implement tool calling with Foundry Local models | https://learn.microsoft.com/en-us/azure/foundry-local/how-to/how-to-use-tool-calling-with-foundry-local |
| Foundry Local REST API reference for local inference | https://learn.microsoft.com/en-us/azure/foundry-local/reference/reference-rest |
| Reference for Foundry Local SDKs in C#, JS, Python, Rust | https://learn.microsoft.com/en-us/azure/foundry-local/reference/reference-sdk-current |
| Legacy Foundry Local SDK reference and CLI-dependent APIs | https://learn.microsoft.com/en-us/azure/foundry-local/reference/reference-sdk-legacy |
Convert PyTorch AT_DISPATCH macros to AT_DISPATCH_V2 format in ATen C++ code. Use when porting AT_DISPATCH_ALL_TYPES_AND*, AT_DISPATCH_FLOATING_TYPES*, or other dispatch macros to the new v2 API. For ATen kernel files, CUDA kernels, and native operator implementations.
Write docstrings for PyTorch functions and methods following PyTorch conventions. Use when writing or updating docstrings in PyTorch code.
Statistical models library for Python. Use when you need specific model classes (OLS, GLM, mixed models, ARIMA) with detailed diagnostics, residuals, and inference. Best for econometrics, time series, rigorous inference with coefficient tables. For guided statistical test selection with APA reporting use statistical-analysis.
Answer questions about the AI SDK and help build AI-powered features. Use when developers: (1) Ask about AI SDK functions like generateText, streamText, ToolLoopAgent, embed, or tools, (2) Want to build AI agents, chatbots, RAG systems, or text generation features, (3) Have questions about AI providers (OpenAI, Anthropic, Google, etc.), streaming, tool calling, structured output, or embeddings, (4) Use React hooks like useChat or useCompletion. Triggers on: "AI SDK", "Vercel AI SDK", "generateText", "streamText", "add AI to my app", "build an agent", "tool calling", "structured output", "useChat".
Create an llms.txt file from scratch based on repository structure following the llms.txt specification at https://llmstxt.org/
Use when working directly with the `esm` Python SDK, ESM3 or ESMC model IDs, Forge/Biohub inference clients, or ESMFold2 folding workflows.
Modal is a serverless cloud platform for running Python on demand, including on-demand GPUs. Use when deploying or serving AI/ML models, running GPU-accelerated workloads (training, fine-tuning, inference), serving web endpoints, scheduling batch jobs, or scaling Python code to cloud containers with the Modal SDK.
Use Therapeutics Data Commons through the PyTDC Python package for registry discovery, approved dataset access, task-aware splits, evaluator metrics, benchmark groups, and bounded molecular-oracle workflows.
Take microsoftdocs/microsoft-foundry-local from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.