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Search and discover Claude Code skills and MCP servers from marketplaces, GitHub repositories, and registries to enhance your AI-assisted development workflow.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
192 skills found
Search and discover Claude Code skills and MCP servers from marketplaces, GitHub repositories, and registries to enhance your AI-assisted development workflow.
A nested plugin architecture for Claude Code that optimizes context by dynamically loading playbooks, skills, and agents to save over 90% in token usage.
The foundational skill for the Superpowers methodology. Ensures agents correctly identify and invoke required development skills before starting any task or conversation.
Systematically trace code flows, locate implementations, diagnose performance issues, and map system architecture to understand complex codebases.
Structured, template-driven workflow for end-to-end feature development including coding, automated testing, verification, and session-based improvement.
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.
Anthropic Claude integration patterns: streaming, RAG with pgvector, tool use, model selection (Haiku/Sonnet/Opus), prompt caching, and cost management for AI-powered engineering.
Execute implementation plans using isolated subagents for each task, featuring a rigorous two-stage review process for spec compliance and code quality.
Orchestrate Unity Editor via MCP tools. Enables AI to create GameObjects, edit scripts, manage scenes, and automate testing within Unity projects.
A comprehensive guide and reference for building, orchestrating, and deploying AI agents using the Google Agent Development Kit (ADK).
Build and manage MCP servers using the FastMCP framework. Guide for creating tools, resources, prompts, Claude Desktop integration, and deployment with Python and TypeScript.
Log ideas, notes, and learning progress chronologically to project archives using a CLI helper tool for systematic knowledge retention.