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Found 11 Skills
MUST READ before creating or enhancing any ADK agent project. Use when the user wants to build a new agent (e.g. "build me a search agent") or enhance an existing project (e.g. "add CI/CD to my project", "add RAG").
High-performance vector similarity search engine for RAG and semantic search. Use when building production RAG systems requiring fast nearest neighbor search, hybrid search with filtering, or scalable vector storage with Rust-powered performance.
Framework for state-of-the-art sentence, text, and image embeddings. Provides 5000+ pre-trained models for semantic similarity, clustering, and retrieval. Supports multilingual, domain-specific, and multimodal models. Use for generating embeddings for RAG, semantic search, or similarity tasks. Best for production embedding generation.
Use when working with context management context restore
Implement GraphRAG patterns combining knowledge graphs with retrieval for complex reasoning. Use this skill when building RAG over interconnected data or needing relationship-aware retrieval. Activate when: GraphRAG, knowledge graph, graph retrieval, entity relationships, Neo4j RAG, graph database, connected data.
Expert guidance for LangChain and LangGraph development with Python, covering chain composition, agents, memory, and RAG implementations.
Perform autonomous, multi-step research using the Gemini Deep Research Agent (Interactions API). Supports web search, file/directory context, and resilient streaming.
Complete knowledge domain for Cloudflare Workers AI - Run AI models on serverless GPUs across Cloudflare's global network. Use when: implementing AI inference on Workers, running LLM models, generating text/images with AI, configuring Workers AI bindings, implementing AI streaming, using AI Gateway, integrating with embeddings/RAG systems, or encountering "AI_ERROR", rate limit errors, model not found, token limit exceeded, or neurons exceeded errors. Keywords: workers ai, cloudflare ai, ai bindings, llm workers, @cf/meta/llama, workers ai models, ai inference, cloudflare llm, ai streaming, text generation ai, ai embeddings, image generation ai, workers ai rag, ai gateway, llama workers, flux image generation, stable diffusion workers, vision models ai, ai chat completion, AI_ERROR, rate limit ai, model not found, token limit exceeded, neurons exceeded, ai quota exceeded, streaming failed, model unavailable, workers ai hono, ai gateway workers, vercel ai sdk workers, openai compatible workers, workers ai vectorize
Design or audit AI-first help centers/knowledge bases/FAQs, including taxonomy, article templates, analytics, and AI support (RAG, chatbot, escalation), using 2025-2026 best practices
Convert natural language queries to SQL. Use for database queries, data analysis, and reporting.
This skill generates a comprehensive set of Frequently Asked Questions (FAQs) from the course description, course content, learning graphs, concept lists, MicroSims, and glossary terms to help students understand common questions and prepare content for chatbot integration. Use this skill after course description, learning graph, glossary, and at least 30% of chapter content exist.