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Found 108 Skills
Use Neo4j GenAI Plugin ai.text.* functions and procedures for in-Cypher embedding generation, text completion, structured output, chat, tokenization, and batch ingestion. Covers ai.text.embed(), ai.text.embedBatch(), ai.text.completion(), ai.text.structuredCompletion(), ai.text.aggregateCompletion(), ai.text.chat(), ai.text.tokenCount(), ai.text.chunkByTokenLimit(), and provider configuration for OpenAI, Azure OpenAI, VertexAI, and Amazon Bedrock. Requires CYPHER 25. Replaces deprecated genai.vector.encode(). Use when writing pure-Cypher GraphRAG, embedding nodes in-graph, generating structured maps from prompts, or calling LLMs inside Cypher queries. Does NOT handle neo4j-graphrag Python library pipelines — use neo4j-graphrag-skill. Does NOT handle vector index creation/search — use neo4j-vector-index-skill.
HertzFlow on-chain trade-decision intelligence. Currently covers Binance Alpha forensic across all surf-SQL EVM chains (BSC / Ethereum / Arbitrum / Base / Polygon / Optimism) — insider distribution, 真实派发 confirmed sell-out, 筹码三分法 (operator / CEX pool / verifiable retail), anomaly waves, monitoring exports. Solana runs in HOLDER_SNAPSHOT mode. Auto-trigger whenever the user pastes a raw 0x-prefixed 40-hex EVM CA, a Solana base58 CA, mentions a Binance Alpha token by ticker, or asks about 链上 forensic / 内幕出货 / 派发 / chip structure / quiet insider / Alpha distribution / on-chain dump — even if they don't say "hertzflow" explicitly. Pipeline runs deterministically (~2-10 min per CA depending on activity + surf cache state); LLM only fills narrative slots, never picks the verdict or writes SQL. Perp metrics, bridge audits, and HertzFlow core contract analysis sub-domains are coming — when those ship, this skill will dispatch to them based on input pattern (perp symbol, bridge protocol name, etc.) using the router table below. REQUIRES a Surf account + SURF_API_KEY. New users get 2000 free credits (~6-8 reports) via the HertzFlow private invite. Full forensic costs ~$1.5-3 USD per CA in Surf credits after the free tier runs out.
Create a Mastra project using create-mastra and smoke test the studio in Chrome
Provides patterns to build Retrieval-Augmented Generation (RAG) systems for AI applications with vector databases and semantic search. Use when implementing knowledge-grounded AI, building document Q&A systems, or integrating LLMs with external knowledge bases.
Consult external LLMs (Gemini, OpenAI/Codex, Qwen) for second opinions, alternative plans, independent reviews, or delegated tasks. Use when a user asks for another model's perspective, wants to compare answers, or requests delegating a subtask to Gemini/Codex/Qwen.
AI integration with Vercel AI SDK - Build AI-powered applications with streaming, function calling, and tool use. Trigger: When implementing AI features, when using useChat or useCompletion, when building chatbots, when integrating LLMs, when implementing function calling.
Expert in the Vercel AI SDK. Covers Core API (generateText, streamText), UI hooks (useChat, useCompletion), tool calling, and streaming UI components with React and Next.js.
Every product will be AI-powered. The question is whether you'll build it right or ship a demo that falls apart in production. This skill covers LLM integration patterns, RAG architecture, prompt engineering that scales, AI UX that users trust, and cost optimization that doesn't bankrupt you. Use when: keywords, file_patterns, code_patterns.
Model Context Protocol (MCP) server development and AI/ML integration patterns. Covers MCP server implementation, tool design, resource handling, and LLM integration best practices. Use when developing MCP servers, creating AI tools, integrating with LLMs, or when asking about MCP protocol, prompt engineering, or AI system architecture.
Guide pour la création de serveurs MCP (Model Context Protocol) de qualité permettant aux LLM d'interagir avec des services externes via des outils bien conçus. À utiliser pour construire des serveurs MCP intégrant des API ou services externes, en Python (FastMCP) ou Node/TypeScript (MCP SDK).
Vercel AI SDK expert guidance. Use when building AI-powered features — chat interfaces, text generation, structured output, tool calling, agents, MCP integration, streaming, embeddings, reranking, image generation, or working with any LLM provider.
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).