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suggest-awesome-github-copilot-agents

npx machina-cli add skill github/awesome-copilot/suggest-awesome-github-copilot-agents --openclaw
Files (1)
SKILL.md
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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    • Agents that are outdated (content differs)
    • Key differences in outdated agents (tools, description, content)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 Present Options: Display relevant custom agents with descriptions, rationale, and availability status including outdated agents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    • Update outdated agents by replacing with latest version from awesome-copilot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 AgentDescriptionAlready InstalledSimilar Local Custom AgentSuggestion Rationale
amplitude-experiment-implementation.agent.mdThis custom agent uses Amplitude's MCP tools to deploy new experiments inside of Amplitude, enabling seamless variant testing capabilities and rollout of product features❌ NoNoneWould enhance experimentation capabilities within the product
launchdarkly-flag-cleanup.agent.mdFeature flag cleanup agent for LaunchDarkly✅ Yeslaunchdarkly-flag-cleanup.agent.mdAlready covered by existing LaunchDarkly custom agents
principal-software-engineer.agent.mdProvide principal-level software engineering guidance with focus on engineering excellence, technical leadership, and pragmatic implementation.⚠️ Outdatedprincipal-software-engineer.agent.mdTools 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

Source

git clone https://github.com/github/awesome-copilot/blob/main/plugins/awesome-copilot/skills/suggest-awesome-github-copilot-agents/SKILL.mdView on GitHub

Overview

This skill analyzes your repository context and chat history to surface relevant Custom Agent files from the awesome-copilot repository. It identifies duplicates, detects outdated agents, and provides a structured list with descriptions and links for quick installation or updates.

How This Skill Works

It fetches the remote agents catalog, scans local .github/agents for existing files, and reads their front matter for descriptions. It then fetches remote versions, compares contents to determine up-to-date versus outdated agents, and presents a structured table with rationale and links. It awaits your direction to install or update any selected agents.

When to Use It

  • You want to augment your repo with Copilot Custom Agents that fit current project needs without duplicates.
  • You need to identify and remove outdated local agents by comparing with the latest from awesome-copilot.
  • You want a prioritized list of agents based on your repository patterns and chat history.
  • You're preparing for installation or updates and want clear rationales and links.
  • You're integrating automation to maintain alignment with the awesome-copilot agent catalog.

Quick Start

  1. Step 1: Run the analysis prompt to fetch remote agents and scan local ones.
  2. Step 2: Review the generated table of suggestions with rationale and links.
  3. Step 3: Respond with the specific agent names to install or update; the system will fetch assets accordingly.

Best Practices

  • Verify the local agent front matter and filename before comparing with remote.
  • Run a full fetch of remote agents via the #fetch tool to ensure freshness.
  • Cross-check descriptions and tool usage to ensure relevance.
  • Avoid installing agents only duplicating existing capabilities.
  • Document any updates in the repository to track changes.

Example Use Cases

  • Suggest an agent for automatic PR description generation not present locally.
  • Identify outdated code-search agent and propose updated version.
  • Propose a test-coverage nudger agent if not already implemented.
  • Recommend a dependency-checker agent based on project type.
  • Propose a language- or framework-specific agent aligned with repository patterns.

Frequently Asked Questions

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