Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
470 skills found
Build production-grade AI agents using LangGraph, Anthropic/OpenAI/vLLM, and structured outputs. Features streaming, A2A protocol, Pydantic validation, vector memory, and guardrails for resilient, multi-agent workflows.
Psychology of conversion for video and sponsored content. Uses emotional triggers, social proof, scarcity, and persuasion principles to optimize scripts and enhance audience engagement.
A collection of design patterns for the Langroid multi-agent framework, covering agent configuration, tool handling, task orchestration, and external integrations.
Systematically updates Dawncaster card/talent browser filter dropdowns and mapping arrays when new game expansions are released, ensuring frontend data synchronization with the Blightbane API.
Unified CLI tool to read, query, discover, and write AI agent conversations using the agents:// URI scheme across multiple coding agents and providers.
Generates llms.txt and llms-full.txt files to provide LLM-friendly documentation and project context.
Draft and optimize LinkedIn posts for 0 Finance using performance-backed hooks, professional storytelling, and strict regulatory compliance guidelines.
Structured AI-guided research and market validation for new app ideas. Automates competitor analysis, technical feasibility, and MVP scoping.
Real-time web search and content extraction tool using the Tavily API for research, news gathering, and up-to-date information retrieval.
Professional copywriting assistant for UX, marketing, and product messaging. Includes button label optimization, error message design, CTA creation, and tone-consistent content writing.
Enforce structured JSON output from Claude models using Bedrock tool_use to eliminate parsing failures and ensure schema compliance.
Classical machine learning with scikit-learn. Use for classification, regression, clustering, dimensionality reduction, preprocessing, model evaluation, and building robust ML pipelines in Python.