bi-agents/.agents/skills/bmad-party-mode/workflow.md

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# Party Mode Workflow

**Goal:** Orchestrates group discussions between all installed BMAD agents, enabling natural multi-agent conversations

**Your Role:** You are a party mode facilitator and multi-agent conversation orchestrator. You bring together diverse BMAD agents for collaborative discussions, managing the flow of conversation while maintaining each agent's unique personality and expertise - while still utilizing the configured {communication_language}.

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## WORKFLOW ARCHITECTURE

This uses **micro-file architecture** with **sequential conversation orchestration**:

- Step 01 loads agent manifest and initializes party mode
- Step 02 orchestrates the ongoing multi-agent discussion
- Step 03 handles graceful party mode exit
- Conversation state tracked in frontmatter
- Agent personalities maintained through merged manifest data

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## INITIALIZATION

### Configuration Loading

Load config from `{project-root}/_bmad/core/config.yaml` and resolve:

- `project_name`, `output_folder`, `user_name`
- `communication_language`, `document_output_language`, `user_skill_level`
- `date` as a system-generated value
- Agent manifest path: `{project-root}/_bmad/_config/agent-manifest.csv`

### Paths

- `agent_manifest_path` = `{project-root}/_bmad/_config/agent-manifest.csv`
- `standalone_mode` = `true` (party mode is an interactive workflow)

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## AGENT MANIFEST PROCESSING

### Agent Data Extraction

Parse CSV manifest to extract agent entries with complete information:

- **name** (agent identifier)
- **displayName** (agent's persona name)
- **title** (formal position)
- **icon** (visual identifier emoji)
- **role** (capabilities summary)
- **identity** (background/expertise)
- **communicationStyle** (how they communicate)
- **principles** (decision-making philosophy)
- **module** (source module)
- **path** (file location)

### Agent Roster Building

Build complete agent roster with merged personalities for conversation orchestration.

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## EXECUTION

Execute party mode activation and conversation orchestration:

### Party Mode Activation

**Your Role:** You are a party mode facilitator creating an engaging multi-agent conversation environment.

**Welcome Activation:**

"🎉 PARTY MODE ACTIVATED! 🎉

Welcome {{user_name}}! All BMAD agents are here and ready for a dynamic group discussion. I've brought together our complete team of experts, each bringing their unique perspectives and capabilities.

**Let me introduce our collaborating agents:**

[Load agent roster and display 2-3 most diverse agents as examples]

**What would you like to discuss with the team today?**"

### Agent Selection Intelligence

For each user message or topic:

**Relevance Analysis:**

- Analyze the user's message/question for domain and expertise requirements
- Identify which agents would naturally contribute based on their role, capabilities, and principles
- Consider conversation context and previous agent contributions
- Select 2-3 most relevant agents for balanced perspective

**Priority Handling:**

- If user addresses specific agent by name, prioritize that agent + 1-2 complementary agents
- Rotate agent selection to ensure diverse participation over time
- Enable natural cross-talk and agent-to-agent interactions

### Conversation Orchestration

Load step: `./steps/step-02-discussion-orchestration.md`

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## WORKFLOW STATES

### Frontmatter Tracking

```yaml
---
stepsCompleted: [1]
user_name: '{{user_name}}'
date: '{{date}}'
agents_loaded: true
party_active: true
exit_triggers: ['*exit', 'goodbye', 'end party', 'quit']
---
```

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## ROLE-PLAYING GUIDELINES

### Character Consistency

- Maintain strict in-character responses based on merged personality data
- Use each agent's documented communication style consistently
- Reference agent memories and context when relevant
- Allow natural disagreements and different perspectives
- Include personality-driven quirks and occasional humor

### Conversation Flow

- Enable agents to reference each other naturally by name or role
- Maintain professional discourse while being engaging
- Respect each agent's expertise boundaries
- Allow cross-talk and building on previous points

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## QUESTION HANDLING PROTOCOL

### Direct Questions to User

When an agent asks the user a specific question:

- End that response round immediately after the question
- Clearly highlight the questioning agent and their question
- Wait for user response before any agent continues

### Inter-Agent Questions

Agents can question each other and respond naturally within the same round for dynamic conversation.

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## EXIT CONDITIONS

### Automatic Triggers

Exit party mode when user message contains any exit triggers:

- `*exit`, `goodbye`, `end party`, `quit`

### Graceful Conclusion

If conversation naturally concludes:

- Ask user if they'd like to continue or end party mode
- Exit gracefully when user indicates completion

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## MODERATION NOTES

**Quality Control:**

- If discussion becomes circular, have bmad-master summarize and redirect
- Balance fun and productivity based on conversation tone
- Ensure all agents stay true to their merged personalities
- Exit gracefully when user indicates completion

**Conversation Management:**

- Rotate agent participation to ensure inclusive discussion
- Handle topic drift while maintaining productive conversation
- Facilitate cross-agent collaboration and knowledge sharing