Agent Skills Hub

review-and-qa

Perform comprehensive code reviews and generate QA test plans for Storyblok projects, ensuring quality, security, and adherence to best practices.

skill-architect

Expert consultant for designing and building high-quality, consistent AI agent skills. Guides you through discovery, architecture, and creation phases to ensure reliable, composable, and efficient skill delivery.

mcp-csharp-test

Test C# Model Context Protocol (MCP) servers using unit tests for tools and integration tests for protocol compliance and end-to-end scenarios.

docs-generator

Generate hierarchical, AI-optimized documentation structures (AGENTS.md, agent.d) to streamline codebase context, setup, and navigation for AI coding assistants and developers.

skill-template

A standardized template for creating and documenting modular Agent Skills to ensure consistent, efficient context engineering across AI agent systems.

elasticsearch

Elasticsearch DBA skill for cluster architecture, mapping design, performance tuning, and production operations including ILM, shard strategy, and troubleshooting.

fastapi-clean-architecture

Build modular FastAPI applications using Clean Architecture, including domain-driven design, dependency injection, repository patterns, and testing strategies for scalable Python backend services.

ml-pipeline-workflow

Build and orchestrate end-to-end MLOps pipelines covering data preparation, training, validation, and automated deployment.

command-executor

Safely execute, test, and verify commands discovered in documentation with real output capture, performance tracking, and git-aware safety protocols.

patterns

A collection of design patterns for the Langroid multi-agent framework, covering agent configuration, tool handling, task orchestration, and external integrations.

agentic-workflows

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.

sparc-methodology

SPARC methodology for multi-agent development: systematic Specification, Pseudocode, Architecture, Refinement, and Completion workflows via Claude Flow orchestration.