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
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- Agents that are outdated (content differs)
- Key differences in outdated agents (tools, description, content)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
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 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
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.