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Found 13,584 Skills
Chat with your agent about projects, recommendations, and canonical papers in Paperzilla. Use when users ask for recent project recommendations, canonical paper details, markdown-based summaries, recommendation feedback, feed export, or Atom feed URLs.
Designs and reviews WebMCP instrumentation for existing web apps, especially SPAs. Use when adding agent-accessible tools, route maps, prompts, or WebMCP workflows to a React, Vue, Angular, or vanilla browser app, or when deciding whether WebMCP is the right fit.
Guide Agents to accurately call taiwan-legal-db and dr-lawbot (semantic precedent retrieval) MCP tools in a hallucination-resistant manner to retrieve Taiwanese laws, precedents, and constitutional judgments, and implement citation verification and trust gates.
Production-ready patterns for building LLM applications. Covers RAG pipelines, agent architectures, prompt IDEs, and LLMOps monitoring. Use when designing AI applications, implementing RAG, building agents, or setting up LLM observability.
Autonomous biomedical AI agent framework for executing complex research tasks across genomics, drug discovery, molecular biology, and clinical analysis. Use this skill when conducting multi-step biomedical research including CRISPR screening design, single-cell RNA-seq analysis, ADMET prediction, GWAS interpretation, rare disease diagnosis, or lab protocol optimization. Leverages LLM reasoning with code execution and integrated biomedical databases.
CloudBase Run backend development rules (Function mode/Container mode). Use this skill when deploying backend services that require long connections, multi-language support, custom environments, or AI agent development.
This skill should be used when working with DSPy.rb, a Ruby framework for building type-safe, composable LLM applications. Use this when implementing predictable AI features, creating LLM signatures and modules, configuring language model providers (OpenAI, Anthropic, Gemini, Ollama), building agent systems with tools, optimizing prompts, or testing LLM-powered functionality in Ruby applications.
Guide for Vercel AI SDK v6 implementation patterns including generateText, streamText, ToolLoopAgent, structured output with Output helpers, useChat hook, tool calling, embeddings, middleware, and MCP integration. Use when implementing AI chat interfaces, streaming responses, agentic applications, tool/function calling, text embeddings, workflow patterns, or working with convertToModelMessages and toUIMessageStreamResponse. Activates for AI SDK integration, useChat hook usage, message streaming, agent development, or tool calling tasks.
Teaches how to interact with the Ray application. This skill should be used when users want to interact with Ray through a coding agent or LLM with skills capabilities.
Orchestrates complete project initialization by coordinating agent-folder-init, linter-formatter-init, husky-test-coverage, and other setup skills. Use this skill when starting a new project that needs full AI-first development infrastructure with code quality enforcement.
Builds LLM applications with LangChain including chains, agents, memory, tools, and RAG pipelines. Use when users request "LangChain setup", "LLM chain", "AI workflow", "conversational AI", or "RAG pipeline".
This skill should be used when the user asks to "create a PRD for Replit", "write product requirements", "document app specifications", "prepare a product spec", or needs a comprehensive specification document that Replit Agent can use for complex, multi-feature applications. Creates structured PRDs optimized for AI-powered development.