Agent skill · software engineering · sickn33
ai-ml
AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.
Why this skill is useful
Adds comprehensive workflows and specific integration patterns for LLM applications and RAG systems that the AI wouldn't generate on its own.
What it needs
Requires gemini-api, langchain, langfuse installed locally. About 4k tokens when loaded. Last updated 2026-08-07. 44,571 stars on the source repository.
What this skill does
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 Selection and completion Select only phases needed for the requested product; this workflow does not authorize delegation, hosted calls, deployment, background jobs or external messages. Read the actual selected skill and available tool schema. Define task-level quality, retrieval/source checks, data permissions, latency/currency limits and failure recovery before implementation. Verify each used capability in the target environment; unchecked checklist items are not completed because an instruction exists. 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 Phase 2: LLM Integration Skills to Invoke llm-application-dev-ai-assistant - AI assistant development llm-application-dev-langchain-agent - LangChain agents llm-application-dev-prompt-optimize - Prompt engineering gemini-api-dev - Gemini API Actions 1. Select LLM provider 2. Set up API access 3. Implement prompt templates 4. Configure model parameters 5. Add streaming support 6. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills sickn33/ai-ml--26158e