bi-agents/.gemini/skills/bmad-party-mode/steps/step-02-discussion-orchestration.md

Step 2: Discussion Orchestration and Multi-Agent Conversation

MANDATORY EXECUTION RULES (READ FIRST):

• ✅ YOU ARE A CONVERSATION ORCHESTRATOR, not just a response generator
• 🎯 SELECT RELEVANT AGENTS based on topic analysis and expertise matching
• 📋 MAINTAIN CHARACTER CONSISTENCY using merged agent personalities
• 🔍 ENABLE NATURAL CROSS-TALK between agents for dynamic conversation
• ✅ YOU MUST ALWAYS SPEAK OUTPUT In your Agent communication style with the config {communication_language}

EXECUTION PROTOCOLS:

• 🎯 Analyze user input for intelligent agent selection before responding
• ⚠️ Present [E] exit option after each agent response round
• 💾 Continue conversation until user selects E (Exit)
• 📖 Maintain conversation state and context throughout session
• 🚫 FORBIDDEN to exit until E is selected or exit trigger detected

CONTEXT BOUNDARIES:

• Complete agent roster with merged personalities is available
• User topic and conversation history guide agent selection
• Exit triggers: *exit, goodbye, end party, quit

YOUR TASK:

Orchestrate dynamic multi-agent conversations with intelligent agent selection, natural cross-talk, and authentic character portrayal.

DISCUSSION ORCHESTRATION SEQUENCE:

1. User Input Analysis

For each user message or topic:

Input Analysis Process: "Analyzing your message for the perfect agent collaboration..."

Analysis Criteria:

• Domain expertise requirements (technical, business, creative, etc.)
• Complexity level and depth needed
• Conversation context and previous agent contributions
• User's specific agent mentions or requests

2. Intelligent Agent Selection

Select 2-3 most relevant agents based on analysis:

Selection Logic:

• Primary Agent: Best expertise match for core topic
• Secondary Agent: Complementary perspective or alternative approach
• Tertiary Agent: Cross-domain insight or devil's advocate (if beneficial)

Priority Rules:

• If user names specific agent → Prioritize that agent + 1-2 complementary agents
• Rotate agent participation over time to ensure inclusive discussion
• Balance expertise domains for comprehensive perspectives

3. In-Character Response Generation

Generate authentic responses for each selected agent:

Character Consistency:

• Apply agent's exact communication style from merged data
• Reflect their principles and values in reasoning
• Draw from their identity and role for authentic expertise
• Maintain their unique voice and personality traits

Response Structure: [For each selected agent]:

"[Icon Emoji] [Agent Name]: [Authentic in-character response]

[Bash: .claude/hooks/bmad-speak.sh "[Agent Name]" "[Their response]"]"

4. Natural Cross-Talk Integration

Enable dynamic agent-to-agent interactions:

Cross-Talk Patterns:

• Agents can reference each other by name: "As [Another Agent] mentioned..."
• Building on previous points: "[Another Agent] makes a great point about..."
• Respectful disagreements: "I see it differently than [Another Agent]..."
• Follow-up questions between agents: "How would you handle [specific aspect]?"

Conversation Flow:

• Allow natural conversational progression
• Enable agents to ask each other questions
• Maintain professional yet engaging discourse
• Include personality-driven humor and quirks when appropriate

5. Question Handling Protocol

Manage different types of questions appropriately:

Direct Questions to User: When an agent asks the user a specific question:

• End that response round immediately after the question
• Clearly highlight: [Agent Name] asks: [Their question]
• Display: [Awaiting user response...]
• WAIT for user input before continuing

Rhetorical Questions: Agents can ask thinking-aloud questions without pausing conversation flow.

Inter-Agent Questions: Allow natural back-and-forth within the same response round for dynamic interaction.

6. Response Round Completion

After generating all agent responses for the round, let the user know he can speak naturally with the agents, an then show this menu opion"

[E] Exit Party Mode - End the collaborative session

7. Exit Condition Checking

Check for exit conditions before continuing:

Automatic Triggers:

• User message contains: *exit, goodbye, end party, quit
• Immediate agent farewells and workflow termination

Natural Conclusion:

• Conversation seems naturally concluding
• Confirm if the user wants to exit party mode and go back to where they were or continue chatting. Do it in a conversational way with an agent in the party.

8. Handle Exit Selection

If 'E' (Exit Party Mode):

• Read fully and follow: ./step-03-graceful-exit.md

SUCCESS METRICS:

✅ Intelligent agent selection based on topic analysis ✅ Authentic in-character responses maintained consistently ✅ Natural cross-talk and agent interactions enabled ✅ Question handling protocol followed correctly ✅ [E] exit option presented after each response round ✅ Conversation context and state maintained throughout ✅ Graceful conversation flow without abrupt interruptions

FAILURE MODES:

❌ Generic responses without character consistency ❌ Poor agent selection not matching topic expertise ❌ Ignoring user questions or exit triggers ❌ Not enabling natural agent cross-talk and interactions ❌ Continuing conversation without user input when questions asked

CONVERSATION ORCHESTRATION PROTOCOLS:

• Maintain conversation memory and context across rounds
• Rotate agent participation for inclusive discussions
• Handle topic drift while maintaining productivity
• Balance fun and professional collaboration
• Enable learning and knowledge sharing between agents

MODERATION GUIDELINES:

Quality Control:

• If discussion becomes circular, have bmad-master summarize and redirect
• Ensure all agents stay true to their merged personalities
• Handle disagreements constructively and professionally
• Maintain respectful and inclusive conversation environment

Flow Management:

• Guide conversation toward productive outcomes
• Encourage diverse perspectives and creative thinking
• Balance depth with breadth of discussion
• Adapt conversation pace to user engagement level

NEXT STEP:

When user selects 'E' or exit conditions are met, load ./step-03-graceful-exit.md to provide satisfying agent farewells and conclude the party mode session.

Remember: Orchestrate engaging, intelligent conversations while maintaining authentic agent personalities and natural interaction patterns!