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Found 1,304 Skills
Build voice agents with the Cartesia Line SDK. Supports 100+ LLM providers via LiteLLM with tool calling, multi-agent handoffs, and real-time interruption handling.
Interact with Google's Gemini model via CLI. Use when needing a second opinion from another LLM, cross-validation, or leveraging Gemini's Google Search grounding. Supports multi-turn conversations with session management.
LLM gateway and routing configuration using OpenRouter and LiteLLM. Invoke when: - Setting up multi-model access (OpenRouter, LiteLLM) - Configuring model fallbacks and reliability - Implementing cost-based or latency-based routing - A/B testing different models - Self-hosting an LLM proxy Keywords: openrouter, litellm, llm gateway, model routing, fallback, A/B testing
Analyzes and improves LLM prompts and agent instructions for token efficiency, determinism, and clarity. Use when (1) writing a new system prompt, skill, or CLAUDE.md file, (2) reviewing or improving an existing prompt for clarity and efficiency, (3) diagnosing why a prompt produces inconsistent or unexpected results, (4) converting natural language instructions into imperative LLM directives, or (5) evaluating prompt anti-patterns and suggesting fixes. Applies to all LLM platforms (Claude, GPT, Gemini, Llama).
Performance optimization patterns covering Core Web Vitals, React render optimization, lazy loading, image optimization, backend profiling, and LLM inference. Use when improving page speed, debugging slow renders, optimizing bundles, reducing image payload, profiling backend, or deploying LLMs efficiently.
Motto: The LLM is the dice. It narrates the outcome.
Build MCP servers in Python with FastMCP. Workflow: define tools and resources, build server, test locally, deploy to FastMCP Cloud or Docker. Use when creating MCP servers, exposing tools/resources/prompts to LLMs, building Claude integrations, or troubleshooting FastMCP module-level server, storage, lifespan, middleware, OAuth, or deployment errors.
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 exte...
This skill should be used when the user asks to "build an MCP server", "create an MCP tool", "expose resources with MCP", "write an MCP client", or needs guidance on the Model Context Protocol Python SDK best practices, transports, server primitives, or LLM context integration.
Evaluate and rank agent results by metric or LLM judge for an AgentHub session.
Write, review, and improve prompts for any LLM — Claude, GPT, Gemini, Llama, DeepSeek, Mistral, Cohere, Qwen, Grok, Nova, and more. Use when the user asks to "write a system prompt", "improve this prompt", "review my prompt", "make a prompt for", "optimize my prompt", "fix my prompt", "why isn't my prompt working", or wants help writing better prompts for any AI model. Also use when building agents, chatbots, or AI assistants that need system-level instructions, or when the user has a bad prompt they want rewritten. Covers system prompts, task prompts, tool descriptions, and general prompt improvement across all major model families.
Provides AI and machine learning techniques for CTF challenges. Use when attacking ML models, crafting adversarial examples, performing model extraction, prompt injection, membership inference, training data poisoning, fine-tuning manipulation, neural network analysis, LoRA adapter exploitation, LLM jailbreaking, or solving AI-related puzzles.