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.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionsuggest-awesome-github-copilot-agentsExecute the skills CLI command in your project's root directory to begin installation:
Fetches suggest-awesome-github-copilot-agents from github/awesome-copilot and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate suggest-awesome-github-copilot-agents. Access via /suggest-awesome-github-copilot-agents in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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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.
fetch tool..github/agents/ folderhttps://raw.githubusercontent.com/github/awesome-copilot/main/agents/<filename>).github/agents/ folder#fetch tool to download assets, but may use curl using #runInTerminal tool to ensure all content is retrieved#todos tool to track progress🔍 Repository Patterns:
🗨️ Chat History Context:
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 |
*.agent.md files in .github/agents/ directorydescriptionhttps://raw.githubusercontent.com/github/awesome-copilot/main/agents/<filename>fetch toolgithubRepo tool to get content from awesome-copilot repository agents folder.github/agents/ directoryWhen outdated agents are identified:
.github/agents/ directoryMake data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
github/awesome-copilot
github/awesome-copilot
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
I recommend suggest-awesome-github-copilot-agents for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Keeps context tight: suggest-awesome-github-copilot-agents is the kind of skill you can hand to a new teammate without a long onboarding doc.
suggest-awesome-github-copilot-agents fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Keeps context tight: suggest-awesome-github-copilot-agents is the kind of skill you can hand to a new teammate without a long onboarding doc.
We added suggest-awesome-github-copilot-agents from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
I recommend suggest-awesome-github-copilot-agents for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Useful defaults in suggest-awesome-github-copilot-agents — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
suggest-awesome-github-copilot-agents is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Registry listing for suggest-awesome-github-copilot-agents matched our evaluation — installs cleanly and behaves as described in the markdown.
suggest-awesome-github-copilot-agents is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
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