multi-agent-workflow（多 Agent 工作流程）

Multi-Agent Workflow Guide

When to use

• Complex feature spanning multiple domains (full-stack, mobile)
• Coordination needed between frontend, backend, mobile, and QA
• User wants step-by-step guidance for multi-agent coordination

When NOT to use

• Simple single-domain task -> use the specific agent directly
• User wants automated execution -> use orchestrator
• Quick bug fixes or minor changes

Core Rules

1. Always start with PM Agent for task decomposition
2. Spawn independent tasks in parallel (same priority tier)
3. Define API contracts before frontend/mobile tasks
4. QA review is always the final step
5. Assign separate workspaces to avoid file conflicts
6. Always use Serena MCP tools as the primary method for code exploration and modification
7. Never skip steps in the workflow — follow each step sequentially without omission

Workflow

Step 1: Plan with PM Agent

PM Agent analyzes requirements, selects tech stack, creates task breakdown with priorities.

Step 2: Spawn Agents by Priority

Spawn agents via CLI:

1. Use spawn-agent.sh for each task
2. CLI selection follows agent_cli_mapping in user-preferences.yaml
3. Spawn all same-priority tasks in parallel using background processes

# Example: spawn backend and frontend in parallel
oh-my-ag agent:spawn backend "task description" session-id -w ./backend &
oh-my-ag agent:spawn frontend "task description" session-id -w ./frontend &
wait

Step 3: Monitor & Coordinate

• Use memory read tool to poll progress-{agent}.md files
• Verify API contracts align between agents
• Ensure shared data models are consistent

Step 4: QA Review

Spawn QA Agent last to review all deliverables. Address CRITICAL issues by re-spawning agents.

Automated Alternative

For fully automated execution without manual spawning, use the orchestrator skill instead.

References

• Workflow examples: resources/examples.md