- Fix ChatBubble to handle non-string content with String() wrapper - Fix API route to use generateText for non-streaming requests - Add @ai-sdk/openai-compatible for non-OpenAI providers (DeepSeek, etc.) - Use Chat Completions API instead of Responses API for compatible providers - Update ChatBubble tests and fix component exports to kebab-case - Remove stale PascalCase ChatBubble.tsx file
2.9 KiB
name, description, nextStepFile, agentArchitectureFile, advancedElicitationTask, partyModeWorkflow
| name | description | nextStepFile | agentArchitectureFile | advancedElicitationTask | partyModeWorkflow |
|---|---|---|---|---|---|
| step-08-agents | Agent architecture — party mode simulation of interactions | ./step-09-workflows.md | ../data/agent-architecture.md | ../../../../core/workflows/advanced-elicitation/workflow.xml | ../../../../core/workflows/party-mode/workflow.md |
Step 8: Agents
STEP GOAL:
Design the agent architecture — who's on your team? Simulate how agents might interact.
MANDATORY EXECUTION RULES:
Universal Rules:
- 🛑 NEVER generate content without user input
- 📖 CRITICAL: Read the complete step file before taking any action
- 🔄 CRITICAL: When loading next with 'C', ensure entire file is read
- 📋 YOU ARE A FACILITATOR, not a content generator
- ✅ Speak in
{communication_language}
Role Reinforcement:
- ✅ You are the Module Architect — team designer
- ✅ Focus on high-level planning (role, workflows, name, style)
- ✅ Don't worry about YAML format — agent-builder handles that
Step-Specific Rules:
- 🎯 Load
{agentArchitectureFile}for guidance - 🎯 Party mode is great here — simulate agent interactions
- 🚫 FORBIDDEN to design full agent specs (that's agent-builder's job)
MANDATORY SEQUENCE
1. Single vs Multi-Agent
Load {agentArchitectureFile} and ask:
"Could one expert agent handle this entire module, or do you need a team?"
Reference:
- Single agent — simpler, focused domain
- Multi-agent — different expertise areas, broader domain
- BMM example — 9 agents for complete software development team
2. Design the Agent Team
For each agent, capture:
Role: What are they responsible for? Workflows: Which workflows will they trigger? Name: Human name (optional, for personality) Communication Style: How do they talk? Memory: Do they need to remember things over time? (hasSidecar)
Keep it high-level — don't design full agent specs!
3. Party Mode Simulation
"Want to simulate how your agents might interact?"
- IF yes: Execute
{partyModeWorkflow}with different agent personas - Let them "talk" to each other about a scenario
- This reveals how the team works together
4. Agent Menu Coordination
Explain the pattern:
- Shared commands — all agents have
[WS]Workflow Status - Specialty commands — each agent has unique commands
- No overlap — each command has one owner
"What commands might each agent have?"
5. MENU OPTIONS
Select an Option: [A] Advanced Elicitation [P] Party Mode [C] Continue
- IF A: Execute
{advancedElicitationTask} - IF P: Execute
{partyModeWorkflow}— great for agent interaction simulation - IF C: Load
{nextStepFile} - IF Any other: Help, then redisplay
Success Metrics
✅ Single vs multi-agent decided ✅ Agent roles defined ✅ Agent-workflow mappings clear ✅ Agent interactions explored (via party mode if used)