| name | repo-agents-pack |
| description | Generate AGENTS.md — agent configuration documentation for any repository. Detects skills, MCP servers, and workflows from repo structure, then produces an actionable agent configuration file that teaches AI agents how to work with the codebase. Use when users want to create agent-compatible documentation, configure Copilot for a repo, or set up MCP server integration. |
| compatibility | Works with any Git repository. Pairs with the repo-onboarding-pack skill. Uses Microsoft Learn MCP Server (https://learn.microsoft.com/api/mcp) for Microsoft technology verification. Integrates with GitHub Copilot SDK (@github/copilot-sdk). |
Repo Agents Pack Generator
Create AGENTS.md — a structured agent configuration document that teaches AI agents (GitHub Copilot, custom agents) how to work effectively with a repository.
Trigger Phrases
This skill activates when users say things like:
- "Generate agents config for this repo"
- "Create AGENTS.md for this project"
- "Configure Copilot skills for this repo"
- "What MCP servers should this repo use?"
- "Set up agent workflows for this codebase"
- "Create agent onboarding docs"
What This Skill Generates
| Document | Purpose |
|---|
AGENTS.md | Skills, MCP servers, and workflows for AI agents working with this repo |
Relationship to Other Skills
This skill is invoked automatically by repo-onboarding-pack as part of the 9-step pipeline (AGENTS.md is generated in step 7: Compile). It can also be used standalone when users only need agent configuration.
AGENTS.md Structure
Required Sections
| Section | Content | Minimum |
|---|
| Header | Project name and one-line description | Must name actual project |
| Skills | Table of agent skills with triggers | At least 1 skill per detected language |
| MCP Servers | Configured MCP servers with tool lists | microsoft-learn always included |
| Workflows | Step-by-step workflows agents should follow | At least 1 (onboarding workflow) + code-review |
| How to Use with GitHub Copilot | Example prompts for using Copilot with the repo | 5+ example prompts |
Output Template
# {projectName} — Agent Configuration
{One-sentence description of the project and its tech stack.}
## Skills
| Skill | Description | Triggers |
|-------|-------------|----------|
| {name} | {what it does} | {comma-separated trigger phrases} |
## MCP Servers
### {server-name}
**URL:** `{server-url}`
**Tools:** `{tool1}`, `{tool2}`, `{tool3}`
## Workflows
### {workflow-name}
{Description}
1. {Step 1}
2. {Step 2}
3. {Step 3}
Workflow
Step 1: Detect Skills from Repository
Analyze the repository to identify agent skills. Each skill represents a capability an AI agent should have when working with this codebase.
Build System Skills
| Build File | Skill Name | Triggers |
|---|
package.json (npm) | npm-build | build, install dependencies, compile |
*.csproj (.NET) | dotnet-build | build, restore packages, compile |
Cargo.toml (Rust) | cargo-build | build, compile, check |
go.mod (Go) | go-build | build, compile, test |
requirements.txt / pyproject.toml | python-build | install deps, build, package |
Makefile | make-build | build, compile, clean |
Test Framework Skills
| Detection | Skill Name | Triggers |
|---|
| Jest / Vitest / Mocha | test-runner | run tests, test coverage, check tests |
| pytest / unittest | python-test | run tests, pytest, coverage |
| xUnit / NUnit / MSTest | dotnet-test | run tests, dotnet test |
| Go test | go-test | run tests, go test |
Language-Specific Skills
For each detected language (top 3 by file count), generate a development skill:
{language-lowercase}-development
Description: Develop and review {Language} code
Triggers: write {Language}, review {Language}, refactor {Language}
Microsoft Technology Skills
When Microsoft technologies are detected, add specialized skills:
| Detection | Skill | Triggers |
|---|
@azure/* packages | azure-services | deploy, configure Azure, manage resources |
.bicep files | infrastructure | deploy infrastructure, Bicep, IaC |
host.json (Functions) | azure-functions | deploy function, add trigger, test function |
Microsoft.SemanticKernel | semantic-kernel | AI plugins, kernel, agents |
@microsoft/microsoft-graph | graph-api | Graph queries, user data, Teams |
Step 2: Detect MCP Servers
Identify MCP servers the repository should connect to.
Always Include
### microsoft-learn
**URL:** `https://learn.microsoft.com/api/mcp`
**Tools:** `microsoft_docs_search`, `microsoft_docs_fetch`, `microsoft_code_sample_search`
Conditional MCP Servers
| Detection | MCP Server | Tools |
|---|
.mcp.json exists in repo | Parse and include all configured servers | As configured |
| Azure dependencies detected | Suggest Azure MCP if not already configured | Azure resource tools |
| GitHub Actions detected | Suggest GitHub MCP | PR, issue, workflow tools |
Step 3: Detect Workflows
Generate step-by-step workflows that agents should follow for common tasks.
Required Workflow: Onboarding
Always generate this workflow:
### onboarding
New contributor onboarding workflow
1. Clone repository
2. Install dependencies
3. Run tests
4. Read ONBOARDING.md
Conditional Workflows
| Detection | Workflow | Steps |
|---|
| Always included | onboarding | Clone → Install → Test → Read docs |
| Always included | code-review | Read PR → Review diff → Check style → Verify tests → Run tests → Give feedback |
| Build scripts present | development | Create branch → Make changes → Run tests → Build → Submit PR |
| CI config detected | ci-cd | Push to branch → CI tests → CI build → Deploy on merge |
| Docker/container files | containerization | Build image → Run locally → Test → Push to registry |
.bicep / azuredeploy.json | infrastructure | Edit Bicep → Validate → What-if → Deploy |
Notebook files (.ipynb) | experimentation | Create notebook → Run cells → Review output → Export results |
Step 4: Quality Validation
After generating AGENTS.md, verify:
| Check | Pass Criteria |
|---|
| Skills count | At least 1 per detected language + 1 for build system |
| Skill triggers | Each skill has 2+ trigger phrases |
| MCP servers | microsoft-learn is always present |
| Workflows | At least 1 workflow (onboarding) |
| File references | No fabricated file paths |
| Technology names | Match actual detected dependencies |
Quality Checklist
Before completing, verify:
Example Output
For a TypeScript + Azure Functions repository:
# my-azure-functions — Agent Configuration
Agent configuration for my-azure-functions — a TypeScript project with 24 dependencies.
## Skills
| Skill | Description | Triggers |
|-------|-------------|----------|
| npm-build | Build and manage the npm project | build, install dependencies, compile |
| test-runner | Run tests using jest | run tests, test coverage, check tests |
| typescript-development | Develop and review TypeScript code | write TypeScript, review TypeScript, refactor TypeScript |
| azure-functions | Deploy and manage Azure Functions | deploy function, add trigger, test function |
## MCP Servers
### microsoft-learn
**URL:** `https://learn.microsoft.com/api/mcp`
**Tools:** `microsoft_docs_search`, `microsoft_docs_fetch`, `microsoft_code_sample_search`
## Workflows
### onboarding
New contributor onboarding workflow
1. Clone repository
2. Install dependencies
3. Run tests
4. Read ONBOARDING.md
### development
Standard development workflow
1. Create feature branch
2. Make changes
3. Run tests
4. Build project
5. Submit PR
### ci-cd
Continuous integration and deployment
1. Push to branch
2. CI runs tests
3. CI runs build
4. Deploy on merge to main
### code-review
Structured code review workflow for learning and quality assurance
1. Open the pull request and read the description
2. Review the diff file-by-file, starting with tests
3. Check code style and naming conventions
4. Verify tests cover the changes
5. Run the test suite locally
6. Leave constructive feedback with specific suggestions
## How to Use with GitHub Copilot
This repository is configured for GitHub Copilot Agent Mode. Use these example prompts in VS Code:
| Goal | Example Prompt |
|------|---------------|
| Understand the project | "Explain the architecture of this project" |
| Start a task | "Help me work on Task 1 from TASKS.md" |
| Review code | "Review the changes in my current branch" |
| Find documentation | "What does the API do?" |
| Debug an issue | "Why is this test failing?" |
| Learn a concept | "Explain how error handling works in this codebase" |
> **Tip:** Open the onboarding docs (ONBOARDING.md, RUNBOOK.md, TASKS.md) as context when chatting with Copilot for better answers.
Agent Invocation
User: "Generate agents config for this repo"
Agent:
- Scan repository (or reuse metadata from repo-onboarding-pack)
- Detect skills from languages, build system, test frameworks
- Detect MCP servers from
.mcp.json and technology analysis
- Generate workflows from build scripts and CI config
- Render AGENTS.md with quality validation
- If Microsoft technologies detected, add specialized skills
References
