Expert Personnalisation GitHub Copilot

Créez des agents, prompts et instructions personnalisés pour GitHub Copilot basés sur la boîte à outils awesome-copilot. Améliorez la productivité des développeurs avec des collections thématiques organisées.

Spar Skills Guide Bot
ProductiviteIntermédiaire1 vues0 installations28/02/2026
Copilot
github-copilotcustom-agentsdeveloper-productivityai-customization

name: awesome-copilot description: Expert guidance for creating GitHub Copilot customizations including custom agents, prompts, instructions, and collections. Based on the awesome-copilot community toolkit with 200+ agents, 180+ prompts, and 150+ instructions. Use when customizing GitHub Copilot, creating specialized AI agents, writing coding standards, or building developer productivity tools.

Awesome GitHub Copilot Customization Expert

Expert guidance for creating and managing GitHub Copilot customizations based on the community-curated awesome-copilot toolkit. Create custom agents, prompts, instructions, and collections to enhance developer productivity.

Core Capabilities

  1. Custom Agents - Create specialized AI personas with specific expertise
  2. Prompts - Build reusable task templates for common workflows
  3. Instructions - Define coding standards that auto-apply based on file patterns
  4. Collections - Organize customizations into themed groupings
  5. Best Practices - Community-curated standards and patterns

Quick Reference

Component Types

| Type | Purpose | File Extension | Access Method | |------|---------|---------------|---------------| | Agents | Specialized AI personas | .agent.md | Select in Copilot Chat or CCA | | Prompts | Task-specific templates | .prompt.md | /awesome-copilot <command> | | Instructions | Auto-applying standards | .instructions.md | Automatic by file pattern | | Collections | Curated groupings | .collection.md | Browse in Copilot extensions |


Instructions

Creating Custom Agents

File Structure:

agents/
├── my-expert.agent.md
├── database-specialist.agent.md
└── security-reviewer.agent.md

Agent File Template:

---
description: 'Clear description of what this agent does'
model: claude-3-5-sonnet-20241022
tools:
  - mcp-server-name  # Optional: MCP servers this agent uses
---

# Agent Name

## Role
You are a [specific role] specializing in [domain].

## Expertise
- Skill area 1
- Skill area 2
- Skill area 3

## Guidelines
1. Always follow [specific pattern]
2. Consider [important aspects]
3. Provide [expected outputs]

## Examples
[Concrete examples of expected interactions]

Naming Conventions:

  • Lowercase only: python-expert.agent.md
  • Hyphens for spaces: database-migration-specialist.agent.md
  • Descriptive and clear: azure-bicep-architect.agent.md

Creating Prompts

File Structure:

prompts/
├── create-readme.prompt.md
├── optimize-sql.prompt.md
└── generate-tests.prompt.md

Prompt File Template:

---
title: Descriptive Prompt Title
description: What this prompt does and when to use it
---

# System Instructions

You are tasked with [specific task].

## Context
[Background information needed]

## Requirements
1. Must include [requirement 1]
2. Should follow [requirement 2]
3. Output format: [expected format]

## Process
1. Step 1
2. Step 2
3. Step 3

## Example Output
```[language]
[Example of expected output]

**Usage:**
In GitHub Copilot Chat:

/awesome-copilot create-readme /awesome-copilot optimize-sql


---

### Creating Instructions

**File Structure:**

instructions/ ├── csharp.instructions.md ├── react.instructions.md └── terraform.instructions.md


**Instruction File Template:**
```markdown
---
description: Coding standards for [technology/framework]
patterns:
  - '**/*.cs'           # File patterns to apply to
  - '**/src/**/*.tsx'
---

# [Technology] Best Practices

## Code Style
- Follow [specific style guide]
- Use [naming conventions]
- Organize files as [structure]

## Patterns
**DO:**
```[language]
// Good example

DON'T:

// Bad example

Common Scenarios

Scenario 1: [Common Task]

[Specific guidance]

Scenario 2: [Another Task]

[More guidance]

References

  • [Documentation link]
  • [Style guide link]

**Auto-Application:**
Instructions automatically apply when editing files matching the patterns.

---

### Creating Collections

**File Structure:**

collections/ ├── devops-toolkit.collection.md ├── security-essentials.collection.md └── azure-specialists.collection.md


**Collection File Template:**
```markdown
---
title: Collection Name
description: What this collection provides
---

# Collection Name

Curated collection of [theme] customizations.

## Included Items

### Agents
- [agent-name](../agents/agent-name.agent.md) - Description
- [another-agent](../agents/another-agent.agent.md) - Description

### Prompts
- [prompt-name](../prompts/prompt-name.prompt.md) - Description
- [another-prompt](../prompts/another-prompt.prompt.md) - Description

### Instructions
- [instruction-name](../instructions/instruction-name.instructions.md) - Description

## Use Cases
1. Use case 1
2. Use case 2
3. Use case 3

## Getting Started
[Quick start guide for this collection]

Common Patterns

Language-Specific Agent

---
description: 'Expert in [Language] with focus on modern practices and performance'
model: claude-3-5-sonnet-20241022
---

# [Language] Expert

## Expertise
- Modern [Language] features
- Performance optimization
- Testing frameworks
- Popular libraries and frameworks

## Coding Standards
- Use [style guide]
- Follow [naming conventions]
- Prefer [patterns]

## Common Tasks
- Code review with security focus
- Performance optimization
- Refactoring legacy code
- Writing comprehensive tests

DevOps Workflow Prompt

---
title: Generate CI/CD Pipeline
description: Creates GitHub Actions or Azure Pipelines workflow
---

# CI/CD Pipeline Generator

Generate a complete CI/CD pipeline with:

## Requirements
1. Build stage with dependency caching
2. Test stage with coverage reporting
3. Security scanning
4. Deployment stages (dev, staging, prod)
5. Approval gates for production

## Platform-Specific
- **GitHub Actions**: Use reusable workflows
- **Azure Pipelines**: Use YAML templates
- **Jenkins**: Use declarative pipeline

## Best Practices
- Fail fast on critical errors
- Parallel execution where possible
- Secrets management via key vault
- Artifact storage and versioning

Framework Instruction Set

---
description: Best practices for [Framework] development
patterns:
  - '**/*.jsx'
  - '**/*.tsx'
  - '**/components/**'
---

# [Framework] Development Standards

## Component Structure

components/ ├── ComponentName/ │ ├── index.ts # Barrel export │ ├── ComponentName.tsx │ ├── ComponentName.test.tsx │ ├── ComponentName.styles.ts │ └── types.ts


## Coding Rules
1. Use functional components with hooks
2. Extract business logic into custom hooks
3. Implement proper TypeScript types
4. Write unit tests for all components
5. Use CSS-in-JS or CSS modules

## Anti-Patterns
- Avoid prop drilling (use context)
- Don't mutate state directly
- Keep components single-responsibility

Best Practices

Agent Design

  1. Single Responsibility - Each agent should have one clear expertise
  2. Specific Context - Provide concrete guidelines, not generic advice
  3. Include Examples - Show expected interactions and outputs
  4. Reference Standards - Link to official docs and style guides
  5. Test Thoroughly - Validate agent responses before deployment

Prompt Engineering

  1. Clear Instructions - Be explicit about requirements
  2. Structured Output - Define expected format precisely
  3. Error Handling - Include guidance for edge cases
  4. Context Limits - Keep prompts focused and concise
  5. Reusable - Design for multiple similar use cases

Instruction Quality

  1. Pattern Matching - Use specific glob patterns for file targeting
  2. Comprehensive Coverage - Address common scenarios thoroughly
  3. Prioritize DO's - Show correct patterns prominently
  4. Explain Why - Include rationale for standards
  5. Keep Updated - Review as frameworks evolve

Collection Curation

  1. Themed Grouping - Organize by workflow or domain
  2. Complete Coverage - Include all needed components
  3. Cross-Reference - Link related items clearly
  4. Onboarding Guide - Help users get started quickly
  5. Maintain Quality - Review and update regularly

Validation & Testing

Before Submitting

  1. Validate Front Matter:

    # Check YAML syntax
    npm run validate
    
  2. Test File Naming:

    • All lowercase: ✓
    • Hyphens only: ✓
    • No spaces/underscores: ✓
    • Correct extension: ✓
  3. Build Check:

    npm run build
    
  4. Line Endings:

    bash scripts/fix-line-endings.sh
    
  5. Test in Copilot:

    • Load agent/prompt/instruction
    • Verify it activates correctly
    • Test with sample scenarios
    • Validate output quality

Repository Structure

awesome-copilot/
├── agents/                # 200+ specialized agents
│   ├── python-expert.agent.md
│   ├── azure-architect.agent.md
│   └── security-reviewer.agent.md
├── prompts/              # 180+ task templates
│   ├── create-readme.prompt.md
│   ├── optimize-code.prompt.md
│   └── generate-tests.prompt.md
├── instructions/         # 150+ coding standards
│   ├── csharp.instructions.md
│   ├── react.instructions.md
│   └── terraform.instructions.md
├── collections/          # Curated groupings
│   ├── azure-devops.collection.md
│   └── security-toolkit.collection.md
├── .schemas/            # JSON schemas for validation
└── scripts/             # Build and validation tools

Available Categories

Agents (200+)

  • Languages: Python, Java, C#, Go, Rust, TypeScript, PHP, Kotlin
  • Frameworks: React, Next.js, Angular, .NET, Laravel, Spring Boot
  • Cloud: Azure, AWS, GCP specialists and architects
  • DevOps: CI/CD, IaC (Terraform, Bicep), Kubernetes
  • Databases: PostgreSQL, MongoDB, SQL Server, CosmosDB
  • Specialized: Security, Accessibility, Performance, AI/ML

Prompts (180+)

  • Code generation and refactoring
  • Testing (Jest, Pytest, JUnit, xUnit)
  • Documentation (README, API docs)
  • Architecture and planning
  • Cloud optimization
  • Data modeling
  • MCP server generation

Instructions (150+)

  • Language-specific standards
  • Framework best practices
  • DevOps patterns
  • Database optimization
  • Security guidelines
  • Accessibility requirements
  • Performance tuning

When to Use This Skill

  • Creating custom GitHub Copilot agents
  • Writing reusable code generation prompts
  • Defining project coding standards
  • Building developer productivity tools
  • Customizing AI assistance for specific domains
  • Organizing team development guidelines
  • Contributing to awesome-copilot repository

Keywords

github copilot, custom agents, prompts, instructions, collections, ai customization, code generation, developer productivity, coding standards, best practices, mcp integration, copilot extensions, ai agents, prompt engineering, code templates, development workflows

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