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Claude Code Multi-Agent Setup

Production-ready Claude Code configuration with multi-agent orchestration, persistent memory, auto-discovered skills, and automation hooks for building fullstack applications.

Key Features

  • Multi-Agent Orchestration: 8 specialized agents coordinated by a central orchestrator (Ezio)
  • Persistent Memory: Agents retain context and learnings across sessions
  • Auto-Discovered Skills: 60+ technical patterns activated by context keywords
  • Mandatory Rules: 6 protocols enforcing quality, boundaries, and honest feedback
  • Hook Automation: Logging, session archiving, context sharing, and response tracking
  • Slash Commands: /handover, /prepare-pr, /discard-changes

Tech Stack

Layer Technologies
Backend Python 3.11+, FastAPI, PostgreSQL
AI/Agents Claude Code SDK, Google ADK, Vertex AI (Gemini)
Frontend React + TypeScript, Vite, Tailwind CSS, TanStack Query
Cloud Cloud-agnostic (Europe regions preferred)
Infrastructure Terraform, GitHub Actions

Claude Code Architecture

The Two-System Principle

┌─────────────────────────────────────────────────────────────┐
│                    Planning System (Ezio)                   │
│  User Request → Plan → Delegate → Synthesize → Report       │
└─────────────────────────┬───────────────────────────────────┘
                          │
        ┌─────────────────┼──────────────────┐
        ▼                 ▼                  ▼
┌────────────────┐ ┌───────────────┐ ┌───────────────┐
│ Scout: Research│ │ Specialists:  │ │ QA Agents:    │
│ & Exploration  │ │ Implementation│ │ Testing       │
└────────────────┘ └───────────────┘ └───────────────┘

The orchestrator (Ezio) plans and coordinates but never executes directly. Specialists handle implementation with their own context windows.

Agents

Nickname Role Responsibilities
Ezio Main Orchestrator Plans tasks, delegates to specialists, synthesizes results
Scout General Worker Research, codebase exploration, routine tasks
Sage Solution Architect Architecture decisions, design reviews, ADRs
Kai AI Engineer Backend, APIs, AI agents (Python/FastAPI/ADK)
Iris Frontend Engineer UI components, React/TypeScript, accessibility
Devo DevOps Engineer Infrastructure, deployment, CI/CD (Terraform)
Vera QA Tester Testing strategy, test automation, coverage
Luna Frontend QA Component tests, E2E, accessibility audits

Three-Tier Knowledge System

Tier Location Purpose Load Behavior
Memory .claude/memory/ Project context, lessons learned Every session
Docs docs/ Detailed plans, ADRs, guides On-demand
Skills .claude/skills/ Technical patterns, code examples Auto-discovered

Project Structure

.
├── CLAUDE.md                 # Universal context (auto-loaded)
├── PROJECT_GUIDELINES.md     # Coding standards
│
├── .claude/
│   ├── agents/               # 8 agent definitions
│   ├── commands/             # Slash commands (/handover, /prepare-pr, /discard-changes)
│   ├── rules/                # 6 mandatory protocols (auto-loaded)
│   │   ├── boundaries.md
│   │   ├── compression-protocol.md
│   │   ├── honest-feedback-protocol.md
│   │   ├── memory-protocol.md
│   │   ├── pre-work-protocol.md
│   │   └── quality-gates.md
│   │
│   ├── skills/               # 60+ patterns (auto-discovered)
│   │   ├── google-adk-patterns/
│   │   ├── deployment/
│   │   ├── testing-strategy/
│   │   ├── frontend-patterns/
│   │   ├── llm-evaluation/
│   │   ├── llm-observability/
│   │   └── ...
│   │
│   ├── memory/               # Per-agent persistent files
│   ├── hooks/                # Automation scripts (Python/Bash)
│   ├── context/              # Shared inter-agent state
│   └── settings.json         # Hooks & permissions config
│
└── docs/
    ├── ONBOARDING.md         # Comprehensive setup guide
    ├── SKILLS_AND_AGENTS_GUIDE.md
    ├── rules-reference.md
    └── adr/                  # Architecture Decision Records

Rules (Mandatory Protocols)

These are auto-loaded and enforce consistent behavior:

Rule Purpose
boundaries Three-tier permission system (Always Do / Ask First / Never Do)
compression-protocol Summarize findings, use file:line references
honest-feedback Challenge ideas, state confidence levels
memory-protocol STAR format for lessons, keep memory lean
pre-work-protocol Check skills before implementation
quality-gates Code review checklists (cloud-agnostic)

Skills (Auto-Discovered Patterns)

Skills are discovered by keyword mentions. Major domains:

Domain Files Coverage
google-adk-patterns/ 8 ADK agents, events, state, tools, memory
deployment/ 7 Cloud Run, Terraform, OAuth, Cloud Build
testing-strategy/ 13 Unit, integration, E2E, accessibility, security
frontend-patterns/ 9 React, routing, state, forms, animations
llm-evaluation/ 6 DeepEval, RAGAS, Vertex AI evaluation
llm-observability/ 6 Langfuse, Phoenix, OpenLLMetry tracing

Example: Mentioning "ADK event persistence" auto-discovers relevant patterns from google-adk-patterns/.


Hooks and Observability (Optional)

Hooks provide observability, workflow automation, and protocol enforcement. All hooks are optional — customize via .claude/settings.json.

Configured Hooks

Event Script Purpose
SessionStart setup-environment.sh Environment setup, Node/Python activation, orchestrator reminder
PreToolUse[Task] task_context_tracker.py Track agent task lifecycle (start)
PostToolUse[*] tool_trace_logger.py Log all tool calls to JSONL
PostToolUse[Task] task_context_tracker.py Track agent task lifecycle (end)
PostToolUse[Task] context_sharing.py Share context between agents
PostToolUse[Task] agent_response_logger.py Log agent responses and deliverables
SessionEnd session_analytics.py Generate session metrics report
SessionEnd session_archiver.py Archive session data for future reference

Available but Not Configured

Script Recommended Event Purpose
inject_shared_context.py UserPromptSubmit Injects shared context from previous agents into prompts

Output Files

Generated by hooks, safely deletable, and git-ignored:

Location File Generated By
.claude/logs/ tool-trace.jsonl tool_trace_logger.py
.claude/logs/ session-metrics.jsonl session_analytics.py
.claude/logs/ latest-session-report.txt session_analytics.py
.claude/logs/ .active_tasks.json task_context_tracker.py
.claude/context/ shared-context.json context_sharing.py

Customization

  • Disable: Remove entry from .claude/settings.json
  • Enable: Add to appropriate event in settings.json
  • Modify: Edit scripts in .claude/hooks/ (standard stdin/stdout)
  • Hook types: command (shell) or prompt (LLM-powered, Stop events only)

Getting Started

Prerequisites

  • Node.js 18+ (for frontend)
  • Python 3.11+ (for backend)
  • Claude Code CLI installed

Quick Start

# Clone the repository
git clone https://github.com/YOUR_USERNAME/claude-code-setup.git
cd claude-code-setup

# Open Claude Code — everything auto-loads
claude

How It Works

  1. CLAUDE.md loads universal context automatically
  2. Rules in .claude/rules/ enforce protocols on every interaction
  3. Skills in .claude/skills/ are auto-discovered by keyword mentions
  4. Hooks in .claude/hooks/ run on lifecycle events (session start/end, tool use)

Example interaction:

You: "Add a new API endpoint for user profiles"

Ezio: [Plans task with TodoWrite]
    → [Delegates to Scout for codebase research]
    → [Delegates to Kai for implementation]
    → [Reports completion with summary]

Customization

Adding an Agent

  1. Create .claude/agents/new-agent.md with YAML frontmatter
  2. Add to the agent map in CLAUDE.md
  3. Create .claude/memory/memory-new-agent.md

Creating a Skill

  1. Create file in .claude/skills/ with frontmatter:
    ---
    name: Pattern Name
    description: What this covers
    tags: [keyword1, keyword2]
    ---
  2. Add technical patterns with code examples
  3. Skills are auto-discovered by tag keywords

Writing a Rule

  1. Create .claude/rules/new-rule.md
  2. Rules auto-load and enforce mandatory behavior
  3. Use for protocols that must always apply

Documentation

Document Purpose
ONBOARDING.md Comprehensive setup walkthrough
TUTORIAL.md Hands-on tutorial with examples
SKILLS_AND_AGENTS_GUIDE.md Knowledge system deep dive
rules-reference.md Complete rules documentation

Design Philosophy

Simplicity First

  • Build exactly what's needed, nothing more
  • Prefer open source; use managed services only when significantly beneficial
  • Start monolithic, scale when necessary

Honest Feedback Over Validation

  • Agents challenge ideas before validating
  • State confidence levels explicitly
  • Disagree respectfully when warranted

Context Preservation

  • Orchestrator context stays strategic
  • Raw data processing delegated to agents
  • Compression protocol prevents context bloat

License

MIT

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Claude Code Setup for building fullstack applications

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