skills/ai-ready/SKILL.md
Make any repo AI-ready — analyzes your codebase and generates AGENTS.md, copilot-instructions.md, CI workflows, issue templates, and more. Mines your PR review patterns and creates files customized to your stack. USE THIS SKILL when the user asks to "make this repo ai-ready", "set up AI config", or "prepare this repo for AI contributions".
npx skillsauth add williamlimasilva/.copilot ai-readyInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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This skill helps the user install the latest ai-ready SKILL.md by John Papa into their personal skills directory.
Why?: The full ai-ready skill is ~600 lines of detailed instructions that evolve frequently. This wrapper keeps it discoverable here while the source of truth stays in johnpapa/ai-ready — always up to date.
Tell the user to download the latest SKILL.md to their personal skills directory by running one of these commands in their terminal. This will overwrite any existing local copy.
bash / zsh
mkdir -p ~/.copilot/skills/ai-ready
curl -fsSL https://raw.githubusercontent.com/johnpapa/ai-ready/main/skills/ai-ready/SKILL.md \
-o ~/.copilot/skills/ai-ready/SKILL.md
PowerShell
New-Item -ItemType Directory -Force -Path "$HOME/.copilot/skills/ai-ready" | Out-Null
Invoke-WebRequest -UseBasicParsing "https://raw.githubusercontent.com/johnpapa/ai-ready/main/skills/ai-ready/SKILL.md" -OutFile "$HOME/.copilot/skills/ai-ready/SKILL.md"
For reproducible behavior, the user can replace main in the URL with a specific tag or commit SHA.
Suggest the user review the downloaded skill before loading it to confirm it contains expected instructions:
head -20 ~/.copilot/skills/ai-ready/SKILL.md
After the user confirms they've installed it, tell them to reload skills with /skills reload and then say make this repo ai-ready.
Do not run the install command on the user's behalf. The user must run it themselves.
development
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.