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Found 11 Skills
Create architecture solution design decisions for AI agent consistency. Use when the user says "lets create architecture" or "create technical architecture" or "create a solution design"
Research repository analyzing Claude Code CLI Agent architecture, tools, telemetry, and internal mechanisms
Expert in designing and building autonomous AI agents. Masters tool use, memory systems, planning strategies, and multi-agent orchestration. Use when: build agent, AI agent, autonomous agent, tool use, function calling.
Layer agentic capabilities onto a full-stack Eve app — agents, teams, memory, events, chat, and coordination. Use when designing an app where agents are primary actors, not afterthoughts.
Expert in designing and building autonomous AI agents. Masters tool use, memory systems, planning strategies, and multi-agent orchestration. Use when "build agent, AI agent, autonomous agent, tool use, function calling, multi-agent, agent memory, agent planning, langchain agent, crewai, autogen, claude agent sdk, ai-agents, langchain, autogen, crewai, tool-use, function-calling, autonomous, llm, orchestration" mentioned.
(NS) Generate or refresh lean architecture-rules.md for AI agents — stack, layout, patterns, constraints. Use when the user asks for architecture rules, .nextstage-harness/rules/architecture-rules.md, agent conventions, or "document how this repo works for the AI". Do NOT use for business specs (ns-harness-codebase-reverse-spec), brownfield maps (ns-harness-bootstrap-brownfield), or one-off Cursor rules without a full architecture pass.
Expert guidance on AI Agent Harness architecture based on the comprehensive Claude Code analysis book
Use when the user needs to build AI agents — tool use patterns, memory management, planning strategies, multi-agent coordination, evaluation, and safety guardrails. Triggers: user says "agent", "build an agent", "tool use", "agent loop", "multi-agent", "memory management", "guardrails", "agent evaluation".
Expert guidance on AI Agent architecture, harness design patterns, and building production-grade Agent systems based on Claude Code analysis
Persistent memory architecture for AI agents across sessions. Episodic memory (past events), procedural memory (learned skills), semantic memory (knowledge graph), short-term memory (active context). Use when implementing cross-session persistence, skill learning, context preservation, personalization, or building truly adaptive AI systems with long-term memory.
AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.