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microsoft-skill-creator — GitHub Copilot skill

Builds agent skills for Microsoft technologies with Learn MCP research. Use it when you need a reusable knowledge package for Azure, .NET, M365, or VS Code.

Install into GitHub Copilot · Skills CLI (Vercel) All methods and platforms ↓
npx skills add github/awesome-copilot --skill microsoft-skill-creator
Open on GitHub

What microsoft-skill-creator does

The skill researches a chosen Microsoft technology by searching documentation, fetching important pages, and finding code samples. It then asks which areas matter, what agents should do, and which language the examples should target before generating a new skill.

The generated package includes SKILL.md with core knowledge and Learn MCP guidance, plus references/ and sample_codes/ when needed. Foundational concepts, starter code, and common patterns stay local. Large reference material, version-specific details, and task-specific material remain available through lookups.

It works best with Microsoft Learn MCP Server. When that server cannot be used, the skill falls back to mslearn through npx @microsoft/learn-cli or a global package install. Install it if you build Microsoft-focused agent skills repeatedly; it is too much for a one-off documentation question.

What it helps with

  • research a Microsoft technology from official documentation
  • create an agent skill for Azure or .NET
  • find implementation samples through Learn MCP
  • separate local knowledge from dynamic lookups
  • include an mslearn fallback in a generated skill

Example prompts for the agent

  • Create a skill for Azure Service Bus with C# examples.
  • Research Semantic Kernel through Learn MCP and build an agent skill.
  • Build a VS Code skill and use `mslearn` if MCP is unavailable.

How to install microsoft-skill-creator

1Skills CLI (Vercel)

npx skills add github/awesome-copilot --skill microsoft-skill-creator

2GitHub CLI

gh skill install github/awesome-copilot microsoft-skill-creator

3Manually: put the files in place

.github/skills/microsoft-skill-creator/SKILL.md

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Questions about microsoft-skill-creator

How do I install microsoft-skill-creator in GitHub Copilot?

Run npx skills add github/awesome-copilot --skill microsoft-skill-creator. You can also use gh skill install github/awesome-copilot microsoft-skill-creator.

What does microsoft-skill-creator do?

It researches Microsoft technologies from documentation and code examples, then generates a hybrid agent skill. Core material is stored locally while deeper details remain searchable through Learn MCP.

What does microsoft-skill-creator need to work?

Microsoft Learn MCP Server is the preferred option. As a fallback, it uses the mslearn CLI through npx @microsoft/learn-cli or an installed @microsoft/learn-cli package.

Source text

SKILL.md · MIT
---
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`.
```

© github · MIT · github/awesome-copilot

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