Data & AI
microsoft-skill-creator - Claude MCP Skill
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.
SEO Guide: Enhance your AI agent with the microsoft-skill-creator tool. This Model Context Protocol (MCP) server allows Claude Desktop and other LLMs to create agent skills for microsoft technologies using learn mcp tools. use when users want to create ... Download and configure this skill to unlock new capabilities for your AI workflow.
Documentation
SKILL.md# 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/
βββ SKILL.md (required) # Frontmatter (name, description) + instructions
βββ references/ # Documentation loaded into context as needed
βββ sample_codes/ # Working code examples
βββ assets/ # Files used in output (templates, etc.)
```
### Key Principles
- **Frontmatter is critical**: `name` and `description` determine when the skill triggersβbe 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:
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}/
βββ SKILL.md # Core knowledge + Learn MCP guidance
βββ references/ # Detailed local documentation (if needed)
βββ sample_codes/ # Working code examples
βββ getting-started/
βββ 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) | β
Full | |
| Hello world code | β
Full | |
| Common patterns (3-5) | β
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" β purpose, architecture
"{name} getting started quickstart" β setup steps
"{name} API reference" β core classes/methods
"{name} samples examples" β code patterns
"{name} best practices performance" β optimization
```
### For Azure Services
```
"{service} overview features" β capabilities
"{service} quickstart {language}" β setup code
"{service} REST API reference" β endpoints
"{service} SDK {language}" β client library
"{service} pricing limits quotas" β constraints
```
### For Frameworks/Platforms
```
"{framework} architecture concepts" β mental model
"{framework} project structure" β conventions
"{framework} tutorial walkthrough" β end-to-end flow
"{framework} configuration options" β 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/
βββ SKILL.md
βββ sample_codes/
βββ getting-started/
β βββ hello-kernel.cs
βββ common-patterns/
βββ chat-completion.cs
βββ 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")` |
```Signals
Information
- Repository
- github/awesome-copilot
- Author
- github
- Last Sync
- 3/12/2026
- Repo Updated
- 3/12/2026
- Created
- 1/31/2026
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