MR
Mayur Rathi
@github
⭐ 34.1k GitHub stars

Suggest-Awesome-Github-Copilot-Agents

Suggest-Awesome-Github-Copilot-Agents是一款productivity方向的AI技能,核心价值是Suggest relevant GitHub Copilot Custom Agents files from the awesome-copilot repository based on current repository context and chat history, avoiding duplicates with existing custom agents in this re,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。

Suggest relevant GitHub Copilot Custom Agents files from the awesome-copilot repository based on current repository context and chat history, avoiding duplicates with existing custom agents in this re

Last verified on: 2026-05-30
mkdir -p ./skills/suggest-awesome-github-copilot-agents && curl -sfL https://raw.githubusercontent.com/github/awesome-copilot/main/skills/suggest-awesome-github-copilot-agents/SKILL.md -o ./skills/suggest-awesome-github-copilot-agents/SKILL.md

Run in terminal / PowerShell. Requires curl (Unix) or PowerShell 5+ (Windows).

Skill Content

# Suggest Awesome GitHub Copilot Custom Agents


Analyze current repository context and suggest relevant Custom Agents files from the [GitHub awesome-copilot repository](https://github.com/github/awesome-copilot/blob/main/docs/README.agents.md) that are not already available in this repository. Custom Agent files are located in the [agents](https://github.com/github/awesome-copilot/tree/main/agents) folder of the awesome-copilot repository.


Process


1. **Fetch Available Custom Agents**: Extract Custom Agents list and descriptions from [awesome-copilot README.agents.md](https://github.com/github/awesome-copilot/blob/main/docs/README.agents.md). Must use `fetch` tool.

2. **Scan Local Custom Agents**: Discover existing custom agent files in `.github/agents/` folder

3. **Extract Descriptions**: Read front matter from local custom agent files to get descriptions

4. **Fetch Remote Versions**: For each local agent, fetch the corresponding version from awesome-copilot repository using raw GitHub URLs (e.g., `https://raw.githubusercontent.com/github/awesome-copilot/main/agents/<filename>`)

5. **Compare Versions**: Compare local agent content with remote versions to identify:

- Agents that are up-to-date (exact match)

- Agents that are outdated (content differs)

- Key differences in outdated agents (tools, description, content)

6. **Analyze Context**: Review chat history, repository files, and current project needs

7. **Match Relevance**: Compare available custom agents against identified patterns and requirements

8. **Present Options**: Display relevant custom agents with descriptions, rationale, and availability status including outdated agents

9. **Validate**: Ensure suggested agents would add value not already covered by existing agents

10. **Output**: Provide structured table with suggestions, descriptions, and links to both awesome-copilot custom agents and similar local custom agents

**AWAIT** user request to proceed with installation or updates of specific custom agents. DO NOT INSTALL OR UPDATE UNLESS DIRECTED TO DO SO.

11. **Download/Update Assets**: For requested agents, automatically:

- Download new agents to `.github/agents/` folder

- Update outdated agents by replacing with latest version from awesome-copilot

- Do NOT adjust content of the files

- Use `#fetch` tool to download assets, but may use `curl` using `#runInTerminal` tool to ensure all content is retrieved

- Use `#todos` tool to track progress


Context Analysis Criteria


🔍 **Repository Patterns**:


- Programming languages used (.cs, .js, .py, etc.)

- Framework indicators (ASP.NET, React, Azure, etc.)

- Project types (web apps, APIs, libraries, tools)

- Documentation needs (README, specs, ADRs)


🗨️ **Chat History Context**:


- Recent discussions and pain points

- Feature requests or implementation needs

- Code review patterns

- Development workflow requirements


Output Format


Display analysis results in structured table comparing awesome-copilot custom agents with existing repository custom agents:


| Awesome-Copilot Custom Agent | Description | Already Installed | Similar Local Custom Agent | Suggestion Rationale |

| ------------------------------------------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ----------------- | ---------------------------------- | ------------------------------------------------------------- |

| [amplitude-experiment-implementation.ag

🎯 Best For

  • Claude users
  • GitHub Copilot users
  • Knowledge workers
  • Remote teams
  • Professionals

💡 Use Cases

  • Using Suggest-Awesome-Github-Copilot-Agents in daily workflow
  • Automating repetitive productivity tasks

📖 How to Use This Skill

  1. 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. 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. 3

    Apply Suggest-Awesome-Github-Copilot-Agents to Your Work

    Provide context for your task — paste source material, describe your audience, or share existing work to guide the AI.

  4. 4

    Review and Refine

    Edit the AI output for accuracy, tone, and completeness. Add human insight where the AI lacks context.

❓ Frequently Asked Questions

How do I install Suggest-Awesome-Github-Copilot-Agents?

Copy the install command from the Terminal tab and run it. The skill downloads to ./skills/suggest-awesome-github-copilot-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

Not reading the full skill

Skills contain important context and edge cases beyond the quick start.

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