Suggest relevant GitHub Copilot Custom Agents files from the awesome-copilot...

# 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. **Analyze Context**: Review chat history, repository files, and current project needs
5. **Compare Existing**: Check against custom agents already available in this repository
6. **Match Relevance**: Compare available custom agents against identified patterns and requirements
7. **Present Options**: Display relevant custom agents with descriptions, rationale, and availability status
8. **Validate**: Ensure suggested agents would add value not already covered by existing agents
9. **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 of specific custom agents. DO NOT INSTALL UNLESS DIRECTED TO DO SO.
10. **Download Assets**: For requested agents, automatically download and install individual agents to `.github/agents/` folder. Do NOT adjust content of the files. Use `#todos` tool to track progress. Prioritize use of `#fetch` tool to download assets, but may use `curl` using `#runInTerminal` tool to ensure all content is retrieved.

## 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)