Loading...
Loading...
Found 262 Skills
Command-line interface for Ollama - Local LLM inference and model management via Ollama REST API. Designed for AI agents and power users who need to manage models, generate text, chat, and create embeddings without a GUI.
Build container-based Foundry Agents using Azure AI Projects SDK with ImageBasedHostedAgentDefinition. Use when creating hosted agents that run custom code in Azure AI Foundry with your own container images. Triggers: "ImageBasedHostedAgentDefinition", "hosted agent", "container agent", "Foundry Agent", "create_version", "ProtocolVersionRecord", "AgentProtocol.RESPONSES", "custom agent image".
LLM app development with RAG, prompt engineering, vector databases, and AI agents
Migrate supported instruction files, skills, agents, and MCP config into Codex project and global files.
Make websites accessible for AI agents. Navigate, click, type, extract, wait — using Chrome with existing login sessions. No LLM API key needed.
Expert guidance for contributing to and using the Awesome Claude Code repository, a curated collection of Claude Code skills, agents, hooks, and resources.
Microsoft Teams bots and AI agents - Claude/OpenAI, Adaptive Cards, Graph API
Build agents that generate creative content including music, memes, podcasts, and multimedia. Covers generative models, content synthesis, style transfer, and creative control. Use when building creative assistants, automated content creators, multimedia generators, or artistic AI systems.
Engineer effective LLM prompts using zero-shot, few-shot, chain-of-thought, and structured output techniques. Use when building LLM applications requiring reliable outputs, implementing RAG systems, creating AI agents, or optimizing prompt quality and cost. Covers OpenAI, Anthropic, and open-source models with multi-language examples (Python/TypeScript).
Design LLM applications using the LangChain framework with agents, memory, and tool integration patterns. Use when building LangChain applications, implementing AI agents, or creating complex LLM w...
Expert guidance for building production-grade AI agents and workflows using Pydantic AI (the `pydantic_ai` Python library). Use this skill whenever the user is: writing, debugging, or reviewing any Pydantic AI code; asking how to build AI agents in Python with Pydantic; asking about Agent, RunContext, tools, dependencies, structured outputs, streaming, multi-agent patterns, MCP integration, or testing with Pydantic AI; or migrating from LangChain/LlamaIndex to Pydantic AI. Trigger even for vague requests like "help me build an AI agent in Python" or "how do I add tools to my LLM app" — Pydantic AI is very likely what they need.
Browser automation for AI agents via PinchTab HTTP API and CLI — navigate, extract, fill forms, click, scrape, screenshot, export PDF.