Agents
Agents是一款productivity方向的AI技能,核心价值是Guidelines for creating custom agent files for GitHub Copilot,可用于解决开发者在productivity领域的实际问题,帮助用户提升效率、自动化重复任务或优化工作流。
Guidelines for creating custom agent files for GitHub Copilot
mkdir -p ./skills/agents && curl -sfL https://raw.githubusercontent.com/github/awesome-copilot/main/skills/agents/SKILL.md -o ./skills/agents/SKILL.md Run in terminal / PowerShell. Requires curl (Unix) or PowerShell 5+ (Windows).
Skill Content
# Custom Agent File Guidelines
Instructions for creating effective and maintainable custom agent files that provide specialized expertise for specific development tasks in GitHub Copilot.
Project Context
- Target audience: Developers creating custom agents for GitHub Copilot
- File format: Markdown with YAML frontmatter
- File naming convention: lowercase with hyphens (e.g., `test-specialist.agent.md`)
- Location: `.github/agents/` directory (repository-level) or `agents/` directory (organization/enterprise-level)
- Purpose: Define specialized agents with tailored expertise, tools, and instructions for specific tasks
- Official documentation: https://docs.github.com/en/copilot/how-tos/use-copilot-agents/coding-agent/create-custom-agents
Required Frontmatter
Every agent file must include YAML frontmatter with the following fields:
---
description: 'Brief description of the agent purpose and capabilities'
name: 'Agent Display Name'
tools: ['read', 'edit', 'search']
model: 'Claude Sonnet 4.5'
target: 'vscode'
---Core Frontmatter Properties
#### **description** (REQUIRED)
- Single-quoted string, clearly stating the agent's purpose and domain expertise
- Should be concise (50-150 characters) and actionable
- Example: `'Focuses on test coverage, quality, and testing best practices'`
#### **name** (OPTIONAL)
- Display name for the agent in the UI
- If omitted, defaults to filename (without `.md` or `.agent.md`)
- Use title case and be descriptive
- Example: `'Testing Specialist'`
#### **tools** (OPTIONAL)
- List of tool names or aliases the agent can use
- Supports comma-separated string or YAML array format
- If omitted, agent has access to all available tools
- See "Tool Configuration" section below for details
#### **model** (STRONGLY RECOMMENDED)
- Specifies which AI model the agent should use
- Supported in VS Code, JetBrains IDEs, Eclipse, and Xcode
- Example: `'Claude Sonnet 4.5'`, `'gpt-4'`, `'gpt-4o'`
- Choose based on agent complexity and required capabilities
#### **target** (OPTIONAL)
- Specifies target environment: `'vscode'` or `'github-copilot'`
- If omitted, agent is available in both environments
- Use when agent has environment-specific features
#### **user-invocable** (OPTIONAL)
- Boolean controlling whether the agent appears in the agents dropdown in chat
- Default: `true` if omitted
- Set to `false` to create agents that are only accessible as subagents or programmatically
#### **disable-model-invocation** (OPTIONAL)
- Boolean controlling whether the agent can be invoked as a subagent by other agents
- Default: `false` if omitted
- Set to `true` to prevent subagent invocation while keeping it available in the picker
#### **metadata** (OPTIONAL, GitHub.com only)
- Object with name-value pairs for agent annotation
- Example: `metadata: { category: 'testing', version: '1.0' }`
- Not supported in VS Code
#### **mcp-servers** (OPTIONAL, Organization/Enterprise only)
- Configure MCP servers available only to this agent
- Only supported for organization/enterprise level agents
- See "MCP Server Configuration" section below
#### **handoffs** (OPTIONAL, VS Code only)
- Enable guided sequential workflows that transition between agents with suggested next steps
- List of handoff configurations, each specifying a target agent and optional prompt
- After a chat response completes, handoff buttons appear allowing users to move to the next agent
- Only supported in VS Code (version 1.106+)
- See "Handoffs Configuration" section below for details
Handoffs Configuration
Handoffs enable you to create guided sequential workflows that transition seamlessly between custom agents. This is useful for orchestrating multi-step development workflows where users can review and approve each step before moving to the next one.
Common Handoff Patterns
- **Planning → Implementation**: Generate a plan in a planning agent, then hand off to an implementation agent to start coding
- **Implementati
🎯 Best For
- UI designers
- Product designers
- Claude users
- GitHub Copilot users
- Knowledge workers
💡 Use Cases
- Generating component mockups
- Creating design system tokens
- Using Agents in daily workflow
- Automating repetitive productivity tasks
📖 How to Use This Skill
- 1
Install the Skill
Copy the install command from the Terminal tab and run it. The SKILL.md file downloads to your local skills directory.
- 2
Load into Your AI Assistant
Open Claude or GitHub Copilot and reference the skill. Paste the SKILL.md content or use the system prompt tab.
- 3
Apply Agents to Your Work
Provide context for your task — paste source material, describe your audience, or share existing work to guide the AI.
- 4
Review and Refine
Edit the AI output for accuracy, tone, and completeness. Add human insight where the AI lacks context.
❓ Frequently Asked Questions
Does this work with Figma?
Some design skills integrate with Figma plugins. Check the Works With section for supported tools.
How do I install Agents?
Copy the install command from the Terminal tab and run it. The skill downloads to ./skills/agents/SKILL.md, ready to use.
Can I customize this skill for my team?
Absolutely. Edit the SKILL.md file to add team-specific instructions, examples, or workflows.
⚠️ Common Mistakes to Avoid
Skipping usability testing
AI-generated designs should be validated with real users before development.
Not reading the full skill
Skills contain important context and edge cases beyond the quick start.