Suggest Awesome GitHub Copilot Custom Agents

Analyze current repository context and suggest relevant Custom Agents files from the GitHub awesome-copilot repository that are not already available in this repository. Custom Agent files are located in the 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. 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   • Agents that are outdated (content differs)
   • Key differences in outdated agents (tools, description, content)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 Present Options: Display relevant custom agents with descriptions, rationale, and availability status including outdated agents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    • Update outdated agents by replacing with latest version from awesome-copilot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.agent.md | This custom agent uses Amplitude's MCP tools to deploy new experiments inside of Amplitude, enabling seamless variant testing capabilities and rollout of product features | ❌ No | None | Would enhance experimentation capabilities within the product | | launchdarkly-flag-cleanup.agent.md | Feature flag cleanup agent for LaunchDarkly | ✅ Yes | launchdarkly-flag-cleanup.agent.md | Already covered by existing LaunchDarkly custom agents | | principal-software-engineer.agent.md | Provide principal-level software engineering guidance with focus on engineering excellence, technical leadership, and pragmatic implementation. | ⚠️ Outdated | principal-software-engineer.agent.md | Tools configuration differs: remote uses 'web/fetch' vs local 'fetch' - Update recommended |

Local Agent Discovery Process

1. List all *.agent.md files in .github/agents/ directory
2. For each discovered file, read front matter to extract description
3. Build comprehensive inventory of existing agents
4. Use this inventory to avoid suggesting duplicates

Version Comparison Process

1. For each local agent file, construct the raw GitHub URL to fetch the remote version:
   • Pattern: https://raw.githubusercontent.com/github/awesome-copilot/main/agents/<filename>
2. Fetch the remote version using the fetch tool
3. Compare entire file content (including front matter, tools array, and body)
4. Identify specific differences:
   • Front matter changes (description, tools)
   • Tools array modifications (added, removed, or renamed tools)
   • Content updates (instructions, examples, guidelines)
5. Document key differences for outdated agents
6. Calculate similarity to determine if update is needed

Requirements

• Use githubRepo tool to get content from awesome-copilot repository agents folder
• Scan local file system for existing agents in .github/agents/ directory
• Read YAML front matter from local agent files to extract descriptions
• Compare local agents with remote versions to detect outdated agents
• Compare against existing agents in this repository to avoid duplicates
• Focus on gaps in current agent library coverage
• Validate that suggested agents align with repository's purpose and standards
• Provide clear rationale for each suggestion
• Include links to both awesome-copilot agents and similar local agents
• Clearly identify outdated agents with specific differences noted
• Don't provide any additional information or context beyond the table and the analysis

Icons Reference

• ✅ Already installed and up-to-date
• ⚠️ Installed but outdated (update available)
• ❌ Not installed in repo

Update Handling

When outdated agents are identified:

1. Include them in the output table with ⚠️ status
2. Document specific differences in the "Suggestion Rationale" column
3. Provide recommendation to update with key changes noted
4. When user requests update, replace entire local file with remote version
5. Preserve file location in .github/agents/ directory