suggest-awesome-github-copilot-instructions▌
github/awesome-copilot · updated Apr 8, 2026
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Analyze current repository context and suggest relevant copilot-instruction files from the GitHub awesome-copilot repository that are not already available in this repository.
Suggest Awesome GitHub Copilot Instructions
Analyze current repository context and suggest relevant copilot-instruction files from the GitHub awesome-copilot repository that are not already available in this repository.
Process
- Fetch Available Instructions: Extract instruction list and descriptions from awesome-copilot README.instructions.md. Must use
#fetchtool. - Scan Local Instructions: Discover existing instruction files in
.github/instructions/folder - Extract Descriptions: Read front matter from local instruction files to get descriptions and
applyTopatterns - Fetch Remote Versions: For each local instruction, fetch the corresponding version from awesome-copilot repository using raw GitHub URLs (e.g.,
https://raw.githubusercontent.com/github/awesome-copilot/main/instructions/<filename>) - Compare Versions: Compare local instruction content with remote versions to identify:
- Instructions that are up-to-date (exact match)
- Instructions that are outdated (content differs)
- Key differences in outdated instructions (description, applyTo patterns, content)
- Analyze Context: Review chat history, repository files, and current project needs
- Compare Existing: Check against instructions already available in this repository
- Match Relevance: Compare available instructions against identified patterns and requirements
- Present Options: Display relevant instructions with descriptions, rationale, and availability status including outdated instructions
- Validate: Ensure suggested instructions would add value not already covered by existing instructions
- Output: Provide structured table with suggestions, descriptions, and links to both awesome-copilot instructions and similar local instructions AWAIT user request to proceed with installation or updates of specific instructions. DO NOT INSTALL OR UPDATE UNLESS DIRECTED TO DO SO.
- Download/Update Assets: For requested instructions, automatically:
- Download new instructions to
.github/instructions/folder - Update outdated instructions by replacing with latest version from awesome-copilot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 instructions to
Context Analysis Criteria
🔍 Repository Patterns:
- Programming languages used (.cs, .js, .py, .ts, etc.)
- Framework indicators (ASP.NET, React, Azure, Next.js, etc.)
- Project types (web apps, APIs, libraries, tools)
- Development workflow requirements (testing, CI/CD, deployment)
🗨️ Chat History Context:
- Recent discussions and pain points
- Technology-specific questions
- Coding standards discussions
- Development workflow requirements
Output Format
Display analysis results in structured table comparing awesome-copilot instructions with existing repository instructions:
| Awesome-Copilot Instruction | Description | Already Installed | Similar Local Instruction | Suggestion Rationale |
|---|---|---|---|---|
| blazor.instructions.md | Blazor development guidelines | ✅ Yes | blazor.instructions.md | Already covered by existing Blazor instructions |
| reactjs.instructions.md | ReactJS development standards | ❌ No | None | Would enhance React development with established patterns |
| java.instructions.md | Java development best practices | ⚠️ Outdated | java.instructions.md | applyTo pattern differs: remote uses '**/*.java' vs local '*.java' - Update recommended |
Local Instructions Discovery Process
- List all
*.instructions.mdfiles in theinstructions/directory - For each discovered file, read front matter to extract
descriptionandapplyTopatterns - Build comprehensive inventory of existing instructions with their applicable file patterns
- Use this inventory to avoid suggesting duplicates
Version Comparison Process
- For each local instruction file, construct the raw GitHub URL to fetch the remote version:
- Pattern:
https://raw.githubusercontent.com/github/awesome-copilot/main/instructions/<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, applyTo patterns)
- Content updates (guidelines, examples, best practices)
- Document key differences for outdated instructions
- Calculate similarity to determine if update is needed
File Structure Requirements
Based on GitHub documentation, copilot-instructions files should be:
- Repository-wide instructions:
.github/copilot-instructions.md(applies to entire repository) - Path-specific instructions:
.github/instructions/NAME.instructions.md(applies to specific file patterns viaapplyTofrontmatter) - Community instructions:
instructions/NAME.instructions.md(for sharing and distribution)
Front Matter Structure
Instructions files in awesome-copilot use this front matter format:
---
description: 'Brief description of what this instruction provides'
applyTo: '**/*.js,**/*.ts' # Optional: glob patterns for file matching
---
Requirements
- Use
githubRepotool to get content from awesome-copilot repository instructions folder - Scan local file system for existing instructions in
.github/instructions/directory - Read YAML front matter from local instruction files to extract descriptions and
applyTopatterns - Compare local instructions with remote versions to detect outdated instructions
- Compare against existing instructions in this repository to avoid duplicates
- Focus on gaps in current instruction library coverage
- Validate that suggested instructions align with repository's purpose and standards
- Provide clear rationale for each suggestion
- Include links to both awesome-copilot instructions and similar local instructions
- Clearly identify outdated instructions with specific differences noted
- Consider technology stack compatibility and project-specific needs
- 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 instructions 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/instructions/directory
How to use suggest-awesome-github-copilot-instructions 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-instructions
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-instructions 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-instructions. Access the skill through slash commands (e.g., /suggest-awesome-github-copilot-instructions) 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
4.8★★★★★45 reviews- ★★★★★Kabir Smith· Dec 24, 2024
suggest-awesome-github-copilot-instructions is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Aditi Smith· Dec 20, 2024
suggest-awesome-github-copilot-instructions reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Zara Park· Dec 8, 2024
Registry listing for suggest-awesome-github-copilot-instructions matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Zara Ndlovu· Nov 27, 2024
Keeps context tight: suggest-awesome-github-copilot-instructions is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Tariq Thomas· Nov 15, 2024
suggest-awesome-github-copilot-instructions reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Aditi Diallo· Nov 11, 2024
suggest-awesome-github-copilot-instructions is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Kaira Gill· Oct 18, 2024
suggest-awesome-github-copilot-instructions is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Zara Choi· Oct 6, 2024
Registry listing for suggest-awesome-github-copilot-instructions matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Fatima Brown· Oct 2, 2024
Keeps context tight: suggest-awesome-github-copilot-instructions is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Oshnikdeep· Sep 9, 2024
suggest-awesome-github-copilot-instructions is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
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