skills/suggest-awesome-github-copilot-prompts/SKILL.md
Suggest relevant GitHub Copilot prompt files from the awesome-copilot repository based on current repository context and chat history, avoiding duplicates with existing prompts in this repository, and identifying outdated prompts that need updates.
npx skillsauth add williamlimasilva/.copilot suggest-awesome-github-copilot-promptsInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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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.
#fetch tool..github/prompts/ folderhttps://raw.githubusercontent.com/github/awesome-copilot/main/prompts/<filename>).github/prompts/ 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 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| debugging.prompt.md | Debug assistance prompts | ⚠️ Outdated | debugging.prompt.md | Tools configuration differs: remote uses 'codebase' vs local missing - Update recommended |
*.prompt.md files in .github/prompts/ directorydescriptionhttps://raw.githubusercontent.com/github/awesome-copilot/main/prompts/<filename>#fetch toolgithubRepo tool to get content from awesome-copilot repository prompts folder.github/prompts/ directoryWhen outdated prompts are identified:
.github/prompts/ directorydevelopment
Build production RAG pipelines and persistent agent memory using Pinecone as the vector database backend. ALWAYS USE THIS SKILL when the user mentions Pinecone, wants to index documents for semantic search, build a retrieval-augmented generation system, store agent memory across sessions, implement hybrid search, or connect an LLM to a searchable knowledge base — even if they don't say "Pinecone" explicitly. Also use when the user asks about vector databases for RAG, namespace isolation for multi-tenant agents, embedding pipelines, or scaling a knowledge base beyond what local storage can handle. DO NOT use for local-only vector stores (Chroma, FAISS, pgvector) or pure keyword search with no semantic component.
development
Perform an AWS Well-Architected Framework review of the current workload IaC and architecture, generating findings and GitHub issues for improvements.
devops
Query AWS resources using natural language. Covers EC2, S3, RDS, Lambda, ECS, EKS, Secrets Manager, IAM, VPC, networking, messaging, and more. Strictly read-only — no writes, deletes, or mutations.
devops
Analyze AWS resource health, diagnose issues from CloudWatch logs and metrics, and create a remediation plan for identified problems.