microsoft-skill-creator: создание скиллов по Microsoft

--- name: microsoft-skill-creator description: Create agent skills for Microsoft technologies using Learn MCP tools. Use when users want to create a skill that teaches agents about any Microsoft technology, library, framework, or service (Azure, .NET, M365, VS Code, Bicep, etc.). Investigates topics deeply, then generates a hybrid skill storing essential knowledge locally while enabling dynamic deeper investigation. context: fork compatibility: Works best with Microsoft Learn MCP Server (https://learn.microsoft.com/api/mcp). Can also use the mslearn CLI as a fallback. --- # Microsoft Skill Creator Create hybrid skills for Microsoft technologies that store essential knowledge locally while enabling dynamic Learn MCP lookups for deeper details. ## About Skills Skills are modular packages that extend agent capabilities with specialized knowledge and workflows. A skill transforms a general-purpose agent into a specialized one for a specific domain. ### Skill Structure ``` skill-name/ ├── SKILL.md (required) # Frontmatter (name, description) + instructions ├── references/ # Documentation loaded into context as needed ├── sample_codes/ # Working code examples └── assets/ # Files used in output (templates, etc.) ``` ### Key Principles - **Frontmatter is critical**: `name` and `description` determine when the skill triggers—be clear and comprehensive - **Concise is key**: Only include what agents don't already know; context window is shared - **No duplication**: Information lives in SKILL.md OR reference files, not both ## Learn MCP Tools | Tool | Purpose | When to Use | |------|---------|-------------| | `microsoft_docs_search` | Search official docs | First pass discovery, finding topics | | `microsoft_docs_fetch` | Get full page content | Deep dive into important pages | | `microsoft_code_sample_search` | Find code examples | Get implementation patterns | ### CLI Alternative If the Learn MCP server is not available, use the `mslearn` CLI from a terminal or shell (for example, Bash, PowerShell, or cmd) instead: ```bash # Run directly (no install needed) npx @microsoft/learn-cli search "semantic kernel overview" # Or install globally, then run npm install -g @microsoft/learn-cli mslearn search "semantic kernel overview" ``` | MCP Tool | CLI Command | |----------|-------------| | `microsoft_docs_search(query: "...")` | `mslearn search "..."` | | `microsoft_code_sample_search(query: "...", language: "...")` | `mslearn code-search "..." --language ...` | | `microsoft_docs_fetch(url: "...")` | `mslearn fetch "..."` | Generated skills should include this same CLI fallback table so agents can use either path. ## Creation Process ### Step 1: Investigate the Topic Build deep understanding using Learn MCP tools in three phases: **Phase 1 - Scope Discovery:** ``` microsoft_docs_search(query="{technology} overview what is") microsoft_docs_search(query="{technology} concepts architecture") microsoft_docs_search(query="{technology} getting started tutorial") ``` **Phase 2 - Core Content:** ``` microsoft_docs_fetch(url="...") # Fetch pages from Phase 1 microsoft_code_sample_search(query="{technology}", language="{lang}") ``` **Phase 3 - Depth:** ``` microsoft_docs_search(query="{technology} best practices") microsoft_docs_search(query="{technology} troubleshooting errors") ``` #### Investigation Checklist After investigating, verify: - [ ] Can explain what the technology does in one paragraph - [ ] Identified 3-5 key concepts - [ ] Have working code for basic usage - [ ] Know the most common API patterns - [ ] Have search queries for deeper topics ### Step 2: Clarify with User Present findings and ask: 1. "I found these key areas: [list]. Which are most important?" 2. "What tasks will agents primarily perform with this skill?" 3. "Which programming language should code samples prioritize?" ### Step 3: Generate the Skill Use the appropriate template from [skill-templates.md](references/skill-templates.md): | Technology Type | Template | |-----------------|----------| | Client library, NuGet/npm package | SDK/Library | | Azure resource | Azure Service | | App development framework | Framework/Platform | | REST API, protocol | API/Protocol | #### Generated Skill Structure ``` {skill-name}/ ├── SKILL.md # Core knowledge + Learn MCP guidance ├── references/ # Detailed local documentation (if needed) └── sample_codes/ # Working code examples ├── getting-started/ └── common-patterns/ ``` ### Step 4: Balance Local vs Dynamic Content **Store locally when:** - Foundational (needed for any task) - Frequently accessed - Stable (won't change) - Hard to find via search **Keep dynamic when:** - Exhaustive reference (too large) - Version-specific - Situational (specific tasks only) - Well-indexed (easy to search) #### Content Guidelines | Content Type | Local | Dynamic | |--------------|-------|---------| | Core concepts (3-5) | ✅ Full | | | Hello world code | ✅ Full | | | Common patterns (3-5) | ✅ Full | | | Top API methods | Signature + example | Full docs via fetch | | Best practices | Top 5 bullets | Search for more | | Troubleshooting | | Search queries | | Full API reference | | Doc links | ### Step 5: Validate 1. Review: Is local content sufficient for common tasks? 2. Test: Do suggested search queries return useful results? 3. Verify: Do code samples run without errors? ## Common Investigation Patterns ### For SDKs/Libraries ``` "{name} overview" → purpose, architecture "{name} getting started quickstart" → setup steps "{name} API reference" → core classes/methods "{name} samples examples" → code patterns "{name} best practices performance" → optimization ``` ### For Azure Services ``` "{service} overview features" → capabilities "{service} quickstart {language}" → setup code "{service} REST API reference" → endpoints "{service} SDK {language}" → client library "{service} pricing limits quotas" → constraints ``` ### For Frameworks/Platforms ``` "{framework} architecture concepts" → mental model "{framework} project structure" → conventions "{framework} tutorial walkthrough" → end-to-end flow "{framework} configuration options" → customization ``` ## Example: Creating a "Semantic Kernel" Skill ### Investigation ``` microsoft_docs_search(query="semantic kernel overview") microsoft_docs_search(query="semantic kernel plugins functions") microsoft_code_sample_search(query="semantic kernel", language="csharp") microsoft_docs_fetch(url="https://learn.microsoft.com/semantic-kernel/overview/") ``` ### Generated Skill ``` semantic-kernel/ ├── SKILL.md └── sample_codes/ ├── getting-started/ │ └── hello-kernel.cs └── common-patterns/ ├── chat-completion.cs └── function-calling.cs ``` ### Generated SKILL.md ```markdown --- name: semantic-kernel description: Build AI agents with Microsoft Semantic Kernel. Use for LLM-powered apps with plugins, planners, and memory in .NET or Python. --- # Semantic Kernel Orchestration SDK for integrating LLMs into applications with plugins, planners, and memory. ## Key Concepts - **Kernel**: Central orchestrator managing AI services and plugins - **Plugins**: Collections of functions the AI can call - **Planner**: Sequences plugin functions to achieve goals - **Memory**: Vector store integration for RAG patterns ## Quick Start See [getting-started/hello-kernel.cs](sample_codes/getting-started/hello-kernel.cs) ## Learn More | Topic | How to Find | |-------|-------------| | Plugin development | `microsoft_docs_search(query="semantic kernel plugins custom functions")` | | Planners | `microsoft_docs_search(query="semantic kernel planner")` | | Memory | `microsoft_docs_fetch(url="https://learn.microsoft.com/en-us/semantic-kernel/frameworks/agent/agent-memory")` | ## CLI Alternative If the Learn MCP server is not available, use the `mslearn` CLI instead: | MCP Tool | CLI Command | |----------|-------------| | `microsoft_docs_search(query: "...")` | `mslearn search "..."` | | `microsoft_code_sample_search(query: "...", language: "...")` | `mslearn code-search "..." --language ...` | | `microsoft_docs_fetch(url: "...")` | `mslearn fetch "..."` | Run directly with `npx @microsoft/learn-cli <command>` or install globally with `npm install -g @microsoft/learn-cli`. ```