suggest-awesome-github-copilot-skills▌
github/awesome-copilot · updated Apr 14, 2026
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Analyze current repository context and suggest relevant Agent Skills from the GitHub awesome-copilot repository that are not already available in this repository. Agent Skills are self-contained folders located in the skills folder of the awesome-copilot repository, each containing a SKILL.md file with instructions and optional bundled assets.
Suggest Awesome GitHub Copilot Skills
Analyze current repository context and suggest relevant Agent Skills from the GitHub awesome-copilot repository that are not already available in this repository. Agent Skills are self-contained folders located in the skills folder of the awesome-copilot repository, each containing a SKILL.md file with instructions and optional bundled assets.
Process
- Fetch Available Skills: Extract skills list and descriptions from awesome-copilot README.skills.md. Must use
#fetchtool. - Scan Local Skills: Discover existing skill folders in
.github/skills/folder - Extract Descriptions: Read front matter from local
SKILL.mdfiles to getnameanddescription - Fetch Remote Versions: For each local skill, fetch the corresponding
SKILL.mdfrom awesome-copilot repository using raw GitHub URLs (e.g.,https://raw.githubusercontent.com/github/awesome-copilot/main/skills/<skill-name>/SKILL.md) - Compare Versions: Compare local skill content with remote versions to identify:
- Skills that are up-to-date (exact match)
- Skills that are outdated (content differs)
- Key differences in outdated skills (description, instructions, bundled assets)
- Analyze Context: Review chat history, repository files, and current project needs
- Compare Existing: Check against skills already available in this repository
- Match Relevance: Compare available skills against identified patterns and requirements
- Present Options: Display relevant skills with descriptions, rationale, and availability status including outdated skills
- Validate: Ensure suggested skills would add value not already covered by existing skills
- Output: Provide structured table with suggestions, descriptions, and links to both awesome-copilot skills and similar local skills AWAIT user request to proceed with installation or updates of specific skills. DO NOT INSTALL OR UPDATE UNLESS DIRECTED TO DO SO.
- Download/Update Assets: For requested skills, automatically:
- Download new skills to
.github/skills/folder, preserving the folder structure - Update outdated skills by replacing with latest version from awesome-copilot
- Download both
SKILL.mdand any bundled assets (scripts, templates, data files) - 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 skills 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, infrastructure)
- Development workflow requirements (testing, CI/CD, deployment)
- Infrastructure and cloud providers (Azure, AWS, GCP)
🗨️ Chat History Context:
- Recent discussions and pain points
- Feature requests or implementation needs
- Code review patterns
- Development workflow requirements
- Specialized task needs (diagramming, evaluation, deployment)
Output Format
Display analysis results in structured table comparing awesome-copilot skills with existing repository skills:
| Awesome-Copilot Skill | Description | Bundled Assets | Already Installed | Similar Local Skill | Suggestion Rationale |
|---|---|---|---|---|---|
| gh-cli | GitHub CLI skill for managing repositories and workflows | None | ❌ No | None | Would enhance GitHub workflow automation capabilities |
| aspire | Aspire skill for distributed application development | 9 reference files | ✅ Yes | aspire | Already covered by existing Aspire skill |
| terraform-azurerm-set-diff-analyzer | Analyze Terraform AzureRM provider changes | Reference files | ⚠️ Outdated | terraform-azurerm-set-diff-analyzer | Instructions updated with new validation patterns - Update recommended |
Local Skills Discovery Process
- List all folders in
.github/skills/directory - For each folder, read
SKILL.mdfront matter to extractnameanddescription - List any bundled assets within each skill folder
- Build comprehensive inventory of existing skills with their capabilities
- Use this inventory to avoid suggesting duplicates
Version Comparison Process
- For each local skill folder, construct the raw GitHub URL to fetch the remote
SKILL.md:- Pattern:
https://raw.githubusercontent.com/github/awesome-copilot/main/skills/<skill-name>/SKILL.md
- Pattern:
- Fetch the remote version using the
#fetchtool - Compare entire file content (including front matter and body)
- Identify specific differences:
- Front matter changes (name, description)
- Instruction updates (guidelines, examples, best practices)
- Bundled asset changes (new, removed, or modified assets)
- Document key differences for outdated skills
- Calculate similarity to determine if update is needed
Skill Structure Requirements
Based on the Agent Skills specification, each skill is a folder containing:
SKILL.md: Main instruction file with front matter (name,description) and detailed instructions- Optional bundled assets: Scripts, templates, reference data, and other files referenced from
SKILL.md - Folder naming: Lowercase with hyphens (e.g.,
azure-deployment-preflight) - Name matching: The
namefield inSKILL.mdfront matter must match the folder name
Front Matter Structure
Skills in awesome-copilot use this front matter format in SKILL.md:
---
name: 'skill-name'
description: 'Brief description of what this skill provides and when to use it'
---
Requirements
- Use
fetchtool to get content from awesome-copilot repository skills documentation - Use
githubRepotool to get individual skill content for download - Scan local file system for existing skills in
.github/skills/directory - Read YAML front matter from local
SKILL.mdfiles to extract names and descriptions - Compare local skills with remote versions to detect outdated skills
- Compare against existing skills in this repository to avoid duplicates
- Focus on gaps in current skill library coverage
- Validate that suggested skills align with repository's purpose and technology stack
- Provide clear rationale for each suggestion
- Include links to both awesome-copilot skills and similar local skills
- Clearly identify outdated skills with specific differences noted
- Consider bundled asset requirements and compatibility
- 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 skills 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 skill folder with remote version
- Preserve folder location in
.github/skills/directory - Ensure all bundled assets are downloaded alongside the updated
SKILL.md
How to use suggest-awesome-github-copilot-skills 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-skills
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-skills 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-skills. Access the skill through slash commands (e.g., /suggest-awesome-github-copilot-skills) 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★★★★★60 reviews- ★★★★★Arya Khanna· Dec 24, 2024
We added suggest-awesome-github-copilot-skills from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Neel Dixit· Dec 20, 2024
suggest-awesome-github-copilot-skills reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Emma Tandon· Dec 20, 2024
Solid pick for teams standardizing on skills: suggest-awesome-github-copilot-skills is focused, and the summary matches what you get after install.
- ★★★★★Alexander Khan· Dec 20, 2024
suggest-awesome-github-copilot-skills fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Jin Jain· Dec 16, 2024
Registry listing for suggest-awesome-github-copilot-skills matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Emma Smith· Dec 16, 2024
Useful defaults in suggest-awesome-github-copilot-skills — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Li Jain· Nov 15, 2024
suggest-awesome-github-copilot-skills reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Li Menon· Nov 11, 2024
We added suggest-awesome-github-copilot-skills from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Chinedu Farah· Nov 11, 2024
suggest-awesome-github-copilot-skills has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Arjun White· Nov 11, 2024
I recommend suggest-awesome-github-copilot-skills for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
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