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Found 144 Skills
Principal AI Architect and Machine Learning Engineer.
Facebook's library for efficient similarity search and clustering of dense vectors. Supports billions of vectors, GPU acceleration, and various index types (Flat, IVF, HNSW). Use for fast k-NN search, large-scale vector retrieval, or when you need pure similarity search without metadata. Best for high-performance applications.
Build Retrieval-Augmented Generation (RAG) applications that combine LLM capabilities with external knowledge sources. Covers vector databases, embeddings, retrieval strategies, and response generation. Use when building document Q&A systems, knowledge base applications, enterprise search, or combining LLMs with custom data.
Build chat interfaces for querying documents using natural language. Extract information from PDFs, GitHub repositories, emails, and other sources. Use when creating interactive document Q&A systems, knowledge base chatbots, email search interfaces, or document exploration tools.
Orchestrates multi-agent AI systems with task delegation, agent communication, shared memory, and workflow coordination. Use when users request "multi-agent system", "agent orchestration", "AI agents", "agent coordination", or "autonomous agents".
Ollama local LLM deployment and management. Use for running LLMs locally.
Implement agent memory - short-term, long-term, semantic storage, and retrieval
Give your AI agents capabilities through tools (function calling). Helps you identify what your AI needs to do, create tool definitions, and attach them to AI Config variations.
AI/ML APIs, LLM integration, and intelligent application patterns
Patterns and best practices for using Lakebase Provisioned (Databricks managed PostgreSQL) for OLTP workloads.
Develop workflows, custom nodes, and integrations for n8n automation platform
Expert guidance on document chunking strategies for RAG systems. Use this skill when designing how to split documents for vector embeddings. Activate when: chunking, chunk size, text splitting, document segmentation, overlap, semantic chunking, recursive splitting.