ai-ml
AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.
npx skills add majiayu000/claude-skill-registry --skill ai-ml-zidong-ia-biblioteca --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# AI/ML Workflow Bundle ## Overview Comprehensive AI/ML workflow for building LLM applications, implementing RAG systems, creating AI agents, and developing machine learning pipelines. This bundle orchestrates skills for production AI development. ## When to Use This Workflow Use this workflow when: - Building LLM-powered applications - Implementing RAG (Retrieval-Augmented Generation) - Creating AI agents - Developing ML pipelines - Adding AI features to applications - Setting up AI observability ## Workflow Phases ### Phase 1: AI Application Design #### Skills to Invoke - `ai-product` - AI product development - `ai-engineer` - AI engineering - `ai-agents-architect` - Agent architecture - `llm-app-patterns` - LLM patterns #### Actions 1. Define AI use cases 2. Choose appropriate models 3. Design system architecture 4. Plan data flows 5. Define success metrics #### Copy-Paste Prompts ``` Use @ai-product to design AI-powered features ``` ``` Use @ai-agents-architect to design multi-agent system ``` ### Phase 2: LLM Integration #### Skills to Invoke - `llm-application-dev-ai-assistant` - AI assistant development - `llm-application-dev-langchain-agent` - LangChain agents - `llm-applic
- Overview
- When to Use This Workflow
- Workflow Phases
- Phase 1: AI Application Design
- Phase 2: LLM Integration
- Phase 3: RAG Implementation
- Phase 4: AI Agent Development
- Phase 5: ML Pipeline Development
- Phase 6: AI Observability
- Phase 7: AI Security
- AI Development Checklist
- LLM Integration
- RAG System
- AI Agents
What does the ai-ml skill do?
AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill ai-ml-zidong-ia-biblioteca --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.