Agent Skills Hub

request-optimizer

An intelligent gateway that analyzes, scores, and routes user requests across 27 agents, 27 skills, and 14 MCPs to optimize Claude Code execution.

ai-llm-patterns

Anthropic Claude integration patterns: streaming, RAG with pgvector, tool use, model selection (Haiku/Sonnet/Opus), prompt caching, and cost management for AI-powered engineering.

claude-skills

A comprehensive library of 305+ modular instruction packages, Python CLI tools, and agent workflows designed to extend the capabilities of AI coding assistants like Claude Code, Cursor, Aider, and Gemini CLI.

airiot-frontend

Official AIRIOT development toolkit for building React applications with TypeScript, shadcn/ui, and integrated real-time platform capabilities.

subagents-orchestration-guide

Orchestrates multi-agent development workflows, managing task decomposition, requirement analysis, and quality assurance for complex software projects.

jean-claude-dev

Expert development guide for the Jean Claude orchestration framework. Use for source code changes, architecture, testing, and debugging.

deep-thinking

A deep reasoning protocol that ensures systematic analysis, multi-hypothesis generation, and rigorous verification for complex architectural, debugging, and high-stakes tasks.

prompt-writing

Create, refine, and optimize high-quality YAML prompts for AI assistants using structure guidelines, template patterns, and quality standards.

skill-engineer

Orchestrates multi-agent iterative refinement for high-quality OpenClaw skill development, ensuring rigorous testing and lifecycle management.

creating-opencode-agents

Expert guidance and configuration standards for creating specialized OpenCode AI agents, including YAML frontmatter, tool permissions, and operational modes.

context-engineering-collection

A structured repository of Agent Skills for context engineering, multi-agent architectures, and production-grade agent system optimization.

data-engineer

Specialized data engineering agent for designing ETL/ELT pipelines, defining data schemas, managing data quality, and implementing robust ingestion workflows.