suggest-awesome-github-copilot-prompts▌
github/awesome-copilot · updated Apr 8, 2026
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Analyze current repository context and suggest relevant prompt files from the GitHub awesome-copilot repository that are not already available in this repository.
Suggest Awesome GitHub Copilot Prompts
Analyze current repository context and suggest relevant prompt files from the GitHub awesome-copilot repository that are not already available in this repository.
Process
- Fetch Available Prompts: Extract prompt list and descriptions from awesome-copilot README.prompts.md. Must use
#fetchtool. - Scan Local Prompts: Discover existing prompt files in
.github/prompts/folder - Extract Descriptions: Read front matter from local prompt files to get descriptions
- Fetch Remote Versions: For each local prompt, fetch the corresponding version from awesome-copilot repository using raw GitHub URLs (e.g.,
https://raw.githubusercontent.com/github/awesome-copilot/main/prompts/<filename>) - Compare Versions: Compare local prompt content with remote versions to identify:
- Prompts that are up-to-date (exact match)
- Prompts that are outdated (content differs)
- Key differences in outdated prompts (tools, description, content)
- Analyze Context: Review chat history, repository files, and current project needs
- Compare Existing: Check against prompts already available in this repository
- Match Relevance: Compare available prompts against identified patterns and requirements
- Present Options: Display relevant prompts with descriptions, rationale, and availability status including outdated prompts
- Validate: Ensure suggested prompts would add value not already covered by existing prompts
- Output: Provide structured table with suggestions, descriptions, and links to both awesome-copilot prompts and similar local prompts AWAIT user request to proceed with installation or updates of specific prompts. DO NOT INSTALL OR UPDATE UNLESS DIRECTED TO DO SO.
- Download/Update Assets: For requested prompts, automatically:
- Download new prompts to
.github/prompts/folder - Update outdated prompts by replacing with latest version from awesome-copilot
- Do NOT adjust content of the files
- Use
#fetchtool to download assets, but may usecurlusing#runInTerminaltool to ensure all content is retrieved - Use
#todostool to track progress
- Download new prompts to
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 prompts with existing repository prompts:
| Awesome-Copilot Prompt | Description | Already Installed | Similar Local Prompt | Suggestion Rationale |
|---|---|---|---|---|
| code-review.prompt.md | Automated code review prompts | ❌ No | None | Would enhance development workflow with standardized code review processes |
| documentation.prompt.md | Generate project documentation | ✅ Yes | create_oo_component_documentation.prompt.md | Already covered by existing documentation prompts |
| debugging.prompt.md | Debug assistance prompts | ⚠️ Outdated | debugging.prompt.md | Tools configuration differs: remote uses 'codebase' vs local missing - Update recommended |
Local Prompts Discovery Process
- List all
*.prompt.mdfiles in.github/prompts/directory - For each discovered file, read front matter to extract
description - Build comprehensive inventory of existing prompts
- Use this inventory to avoid suggesting duplicates
Version Comparison Process
- For each local prompt file, construct the raw GitHub URL to fetch the remote version:
- Pattern:
https://raw.githubusercontent.com/github/awesome-copilot/main/prompts/<filename>
- Pattern:
- Fetch the remote version using the
#fetchtool - Compare entire file content (including front matter and body)
- Identify specific differences:
- Front matter changes (description, tools, mode)
- Tools array modifications (added, removed, or renamed tools)
- Content updates (instructions, examples, guidelines)
- Document key differences for outdated prompts
- Calculate similarity to determine if update is needed
Requirements
- Use
githubRepotool to get content from awesome-copilot repository prompts folder - Scan local file system for existing prompts in
.github/prompts/directory - Read YAML front matter from local prompt files to extract descriptions
- Compare local prompts with remote versions to detect outdated prompts
- Compare against existing prompts in this repository to avoid duplicates
- Focus on gaps in current prompt library coverage
- Validate that suggested prompts align with repository's purpose and standards
- Provide clear rationale for each suggestion
- Include links to both awesome-copilot prompts and similar local prompts
- Clearly identify outdated prompts 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 prompts are identified:
- Include them in the output table with ⚠️ status
- Document specific differences in the "Suggestion Rationale" column
- Provide recommendation to update with key changes noted
- When user requests update, replace entire local file with remote version
- Preserve file location in
.github/prompts/directory
How to use suggest-awesome-github-copilot-prompts on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add suggest-awesome-github-copilot-prompts
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches suggest-awesome-github-copilot-prompts from GitHub repository github/awesome-copilot and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate suggest-awesome-github-copilot-prompts. Access the skill through slash commands (e.g., /suggest-awesome-github-copilot-prompts) or your agent's skill management interface.
Security & Verification Notice
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 development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
User Story & Requirements Generation
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
Competitive Analysis
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
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
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
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ 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.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.7★★★★★73 reviews- ★★★★★Chaitanya Patil· Dec 28, 2024
Useful defaults in suggest-awesome-github-copilot-prompts — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Anaya Sethi· Dec 28, 2024
suggest-awesome-github-copilot-prompts is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Omar Ndlovu· Dec 16, 2024
Solid pick for teams standardizing on skills: suggest-awesome-github-copilot-prompts is focused, and the summary matches what you get after install.
- ★★★★★Ava Kim· Dec 16, 2024
We added suggest-awesome-github-copilot-prompts from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Naina Lopez· Dec 8, 2024
suggest-awesome-github-copilot-prompts has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Omar Wang· Dec 8, 2024
suggest-awesome-github-copilot-prompts reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Rahul Santra· Nov 27, 2024
Registry listing for suggest-awesome-github-copilot-prompts matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Neel Liu· Nov 27, 2024
Useful defaults in suggest-awesome-github-copilot-prompts — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Piyush G· Nov 19, 2024
suggest-awesome-github-copilot-prompts has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Neel Thompson· Nov 19, 2024
Registry listing for suggest-awesome-github-copilot-prompts matched our evaluation — installs cleanly and behaves as described in the markdown.
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