claude-code-design-guide

What problem does it solve?

It solves the confusion teams face when trying to implement reliable AI agent systems in Claude Code, especially around tool design, context engineering, coordination, and interoperability.

Core Features & Use Cases

• Agent runtime architecture patterns: Understand how the query engine loop, tool calling, and message/state flows work together.
• Tool system design with permissions: Implement safe tool schemas, permission levels, and guardrails for risky operations.
• Context engineering for quality and scalability: Build system prompts, manage CLAUDE.md/project memory, and compact long conversations.
• Multi-agent coordination strategies: Use coordinator patterns and shared memory to handle complex tasks.
• MCP-based tool interoperability: Design MCP servers so tools can be shared across agents and environments.
• Troubleshooting and resilience: Address common failure modes like token overflow, tool execution failures, and permission deadlocks.

Quick Start

Ask an AI engineer to “Use the claude-code-design-guide patterns to design my Claude Code agent’s tool schema, permission model, context/memory strategy, and multi-agent coordination plan.”