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Found 916 Skills
Overcome LLM knowledge cutoffs with real-time developer content. daily.dev aggregates articles from thousands of sources, validated by community engagement, with structured taxonomy for precise discovery.
LangGraph tool calling patterns. Use when binding tools to LLMs, implementing ToolNode for execution, dynamic tool selection, or adding approval gates to tool calls.
Use this skill when working with scientific research tools and workflows across bioinformatics, cheminformatics, genomics, structural biology, proteomics, and drug discovery. This skill provides access to 600+ scientific tools including machine learning models, datasets, APIs, and analysis packages. Use when searching for scientific tools, executing computational biology workflows, composing multi-step research pipelines, accessing databases like OpenTargets/PubChem/UniProt/PDB/ChEMBL, performing tool discovery for research tasks, or integrating scientific computational resources into LLM workflows.
Production-grade fault tolerance for distributed systems. Use when implementing circuit breakers, retry with exponential backoff, bulkhead isolation patterns, or building resilience into LLM API integrations.
LLM observability platform for tracing, evaluation, prompt management, and cost tracking. Use when setting up Langfuse, monitoring LLM costs, tracking token usage, or implementing prompt versioning.
Comprehensive guide for building production-grade LLM applications using LangChain's chains, agents, memory systems, RAG patterns, and advanced orchestration
AI-powered crypto trading agent and LLM gateway via natural language. Use when the user wants to trade crypto, check portfolio balances, view token prices, transfer crypto, manage NFTs, use leverage, bet on Polymarket, deploy tokens, set up automated trading, sign and submit raw transactions, or access LLM models through the Bankr LLM gateway funded by your Bankr wallet. Supports Base, Ethereum, Polygon, Solana, and Unichain.
Design MCP resources to expose content for LLM consumption. Use when creating static or dynamic resources in xmcp.
PocketFlow framework for building LLM applications with graph-based abstractions, design patterns, and agentic coding workflows
OpenInference semantic conventions and instrumentation for Phoenix AI observability. Use when implementing LLM tracing, creating custom spans, or deploying to production.
Guides the agent through building LLM-powered applications with LangChain and stateful agent workflows with LangGraph. Triggered when the user asks to "create an AI agent", "build a LangChain chain", "create a LangGraph workflow", "implement tool calling", "build RAG pipeline", "create a multi-agent system", "define agent state", "add human-in-the-loop", "implement streaming", or mentions LangChain, LangGraph, chains, agents, tools, retrieval augmented generation, state graphs, or LLM orchestration.
Master Moon Dev's Ai Agents Github with 48+ specialized agents, multi-exchange support, LLM abstraction, and autonomous trading capabilities across crypto markets