AI SummaryThis skill provides production-ready operational patterns for designing, building, evaluating, and deploying AI agents. It centralizes procedures, checklists, decision rules, and templates used across RAG agents, tool-using agents, OS agents, and multi-agent systems. No theory. No narrative. Only wh
Install
Copy this and paste it into Claude Code, Cursor, or any AI assistant:
I want to install the "ai-agents" skill in my project. Please run this command in my terminal: # Install skill into your project (2 files) mkdir -p .claude/skills/ai-agents && curl --retry 3 --retry-delay 2 --retry-all-errors -o .claude/skills/ai-agents/SKILL.md "https://raw.githubusercontent.com/majiayu000/claude-skill-registry/main/skills/agent/ai-agents/SKILL.md" && curl --retry 3 --retry-delay 2 --retry-all-errors -o .claude/skills/ai-agents/metadata.json "https://raw.githubusercontent.com/majiayu000/claude-skill-registry/main/skills/agent/ai-agents/metadata.json" Then restart Claude Code (or reload the window in Cursor) so the skill is picked up.
Description
Production-grade AI agent patterns with MCP integration, agentic RAG, handoff orchestration, multi-layer guardrails, and observability (modern best practices)
Navigation: Agent Capabilities
• Agent Operations - resources/agent-operations-best-practices.md Action loops, planning, observation, and execution patterns • RAG Patterns - resources/rag-patterns.md Contextual retrieval, agentic RAG, and hybrid search strategies • Memory Systems - resources/memory-systems.md Session, long-term, episodic, and task memory architectures • Tool Design & Validation - resources/tool-design-specs.md Tool schemas, validation, error handling, and MCP integration
AI Agents Development — Production Skill Hub
Modern Best Practices (December 2025): deterministic control flow, bounded tools, auditable state, MCP-based tool integration, handoff-first orchestration, multi-layer guardrails, OpenTelemetry tracing, and human-in-the-loop controls (OWASP LLM Top 10: https://owasp.org/www-project-top-10-for-large-language-model-applications/). This skill provides production-ready operational patterns for designing, building, evaluating, and deploying AI agents. It centralizes procedures, checklists, decision rules, and templates used across RAG agents, tool-using agents, OS agents, and multi-agent systems. No theory. No narrative. Only what Claude can execute. ---
When to Use This Skill
Claude should activate this skill whenever the user asks for: • Designing an agent (LLM-based, tool-based, OS-based, or multi-agent). • Scoping capability maturity and rollout risk for new agent behaviors. • Creating action loops, plans, workflows, or delegation logic. • Writing tool definitions, MCP tools, schemas, or validation logic. • Generating RAG pipelines, retrieval modules, or context injection. • Building memory systems (session, long-term, episodic, task). • Creating evaluation harnesses, observability plans, or safety gates. • Preparing CI/CD, rollout, deployment, or production operational specs. • Producing any template in /resources/ or /templates/. • Implementing MCP servers or integrating Model Context Protocol. • Setting up agent handoffs and orchestration patterns. • Configuring multi-layer guardrails and safety controls. • For prompt scaffolds, retrieval tuning, or security depth, see Scope Boundaries below.
Scope Boundaries (Use These Skills for Depth)
• Prompt scaffolds & structured outputs → ai-prompt-engineering • RAG retrieval & chunking → ai-rag • Search tuning (BM25/HNSW/hybrid) → ai-rag • Security/guardrails → ai-mlops • Inference optimization → ai-llm-inference ---
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