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 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: "I found these key areas: [list]. Which are most important?" "What tasks will agents primarily perform with this skill?" "Which programming language should code samples prioritize?" Step 3: Generate the Skill Use the appropriate template from 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 Review: Is local content sufficient for common tasks? Test: Do suggested search queries return useful results? 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

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

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") |