production-agent-architect
by Roy Yuen
Architect, scaffold, and harden production-grade AI agents with battle-tested patterns and systematic evaluation.
- Design reliable ReAct agents with strict guardrails and loop detection.
- Scaffold multi-agent systems with explicit handoff and state management.
- Migrate brittle prompts into structured, verifiable agentic workflows.
$6
One-time purchase · Own forever
Included in download
- Design reliable ReAct agents with strict guardrails and loop detection.
- Scaffold multi-agent systems with explicit handoff and state management.
- terminal automation included
- Includes example output and usage patterns
See it in action
ARCHITECTURE: Plan-and-Execute [Planner] -> Task List -> [Executor] -> [Verifier] -> Done GUARDRAILS ENABLED: - Max Iterations: 10 - Schema Validation: Pydantic (Strict) - Cost Limit: $0.10/session METRICS: 92% Succes Rate | 4.2 Avg Steps LOGGING: Full trace enabled via LangSmith
Architect, scaffold, and harden production-grade AI agents with battle-tested patterns and systematic evaluation.
$6
One-time purchase · Own forever
⚡ Also available via Agensi MCP — your AI agent can load this skill on demand via MCP. Learn more →
Included in download
- Design reliable ReAct agents with strict guardrails and loop detection.
- Scaffold multi-agent systems with explicit handoff and state management.
- terminal automation included
- Includes example output and usage patterns
- Instant install
See it in action
ARCHITECTURE: Plan-and-Execute [Planner] -> Task List -> [Executor] -> [Verifier] -> Done GUARDRAILS ENABLED: - Max Iterations: 10 - Schema Validation: Pydantic (Strict) - Cost Limit: $0.10/session METRICS: 92% Succes Rate | 4.2 Avg Steps LOGGING: Full trace enabled via LangSmith
Screenshots
About This Skill
Build Reliable, Production-Grade AI Agents
Designing an agent that works in a demo is easy; building one that survives production is a different challenge. This skill provides a professional framework for architecting, scaffolding, and hardening AI agents and multi-agent systems. It moves beyond simple prompting to implement robust software engineering patterns for LLM-based applications.
What it does
- Architects complex workflows: ReAct, Plan-and-Execute, Reflexion, and multi-agent orchestration.
- Generates production-ready scaffolds using Python, LangChain, CrewAI, AutoGen, or custom loops.
- Implements critical guardrails: max iteration limits, schema validation, cost tracking, and loop detection.
- Designs sophisticated memory systems and state management solutions.
- Builds systematic evaluation suites to move past 'vibe-based' testing to quantifiable metrics.
Why use this skill
Most AI agents fail in production due to infinite loops, tool-calling hallucinations, or lack of observability. This skill automates the implementation of industry-standard design patterns that solve these issues. It ensures your agents are deterministic where needed, cost-effective, and easy to debug by treating agentic logic as a structured system rather than a black box.
Supported Patterns & Tools
- Frameworks: LangChain, CrewAI, AutoGen, LlamaIndex, and Pure Python implementations.
- Patterns: Tool-calling routers, self-critique/verification cycles, and role-based handoffs.
- Infrastructure: Structured logging, LangSmith/Helicone tracing, and Pydantic validation.
Use Cases
- Design reliable ReAct agents with strict guardrails and loop detection.
- Scaffold multi-agent systems with explicit handoff and state management.
- Migrate brittle prompts into structured, verifiable agentic workflows.
- Implement systematic evaluation suites to measure agent success rates.
- Add observability and cost-tracking to existing LLM implementations.
How to Install
unzip production-agent-architect.zip -d ~/.claude/skills/Reviews
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