moai/.planning/phases/06-consensus-export/06-01-PLAN.md

phase	plan	type
06-consensus-export	01	execute

Implement consensus generation for multi-model discussions.

Purpose: Enable users to synthesize discussion outcomes into structured agreements/disagreements (M6 milestone). Output: Working /consensus command that generates and displays AI-summarized consensus.

<execution_context> ~/.claude/get-shit-done/workflows/execute-phase.md ~/.claude/get-shit-done/templates/summary.md </execution_context>

@.planning/PROJECT.md @.planning/ROADMAP.md @.planning/STATE.md

Prior phase context (discussion infrastructure):

@.planning/phases/05-multi-model-discussions/05-03-SUMMARY.md

Source files to modify/reference:

@src/moai/core/models.py @src/moai/core/orchestrator.py @src/moai/core/services/discussion.py @src/moai/bot/handlers/discussion.py @src/moai/bot/handlers/commands.py

Tech stack available: python-telegram-bot, sqlalchemy, openai SDK, asyncio Established patterns: Service layer in core/services/, orchestrator for AI calls, handler delegation to services

Constraining decisions:

• Phase 05-03: build_context() assembles discussion history for AI context
• Phase 05-01: Discussion service with eager loading via selectinload
• Phase 04-01: AI client singleton pattern, MODEL_MAP for short names

SPEC.md consensus format:

• agreements: string[] (bullet points)
• disagreements: [{topic, positions: {model: position}}]
• Consensus model already exists with these fields

Task 1: Add consensus generation to orchestrator and service src/moai/core/orchestrator.py, src/moai/core/services/discussion.py 1. In orchestrator.py, add CONSENSUS_PROMPT constant with instructions to analyze discussion and return JSON with "agreements" (list of strings) and "disagreements" (list of {topic, positions} objects).

2. Add generate_consensus(discussion: Discussion, model: str = "claude") -> dict function:

   • Build context from discussion using existing build_context()
   • Append CONSENSUS_PROMPT as final user message
   • Call AI client with system prompt explaining the task
   • Parse JSON response (handle parsing errors gracefully)
   • Return dict with "agreements" and "disagreements" keys

3. In discussion.py service, add:

   • save_consensus(discussion_id: str, agreements: list, disagreements: list, generated_by: str) -> Consensus
   • get_consensus(discussion_id: str) -> Consensus | None

Use existing session patterns (async with get_session()). Import Consensus model. Python imports succeed: python -c "from moai.core.orchestrator import generate_consensus; from moai.core.services.discussion import save_consensus, get_consensus" generate_consensus() returns dict with agreements/disagreements, save_consensus() persists to DB, get_consensus() retrieves

Task 2: Create /consensus command handler src/moai/bot/handlers/discussion.py, src/moai/bot/handlers/commands.py, src/moai/bot/handlers/__init__.py 1. In discussion.py handlers, add `consensus_command(update, context)`: - Get selected project (error if none) - Get active discussion for project (error if none, suggest /open or /discuss first) - Check if consensus already exists (get_consensus) - if so, display existing - Otherwise call generate_consensus() with discussion - Save consensus via save_consensus() - Format and display: ``` **Consensus Summary**

 **Agreements:**
 - point 1
 - point 2

 **Disagreements:**
 - **Topic:** {topic}
   - Claude: {position}
   - GPT: {position}

 _Generated by {model}_
 ```

• Show typing indicator while generating

2. Register handler in init.py: CommandHandler("consensus", consensus_command)

3. Update HELP_TEXT in commands.py to add consensus under Output section: /consensus - Generate consensus summary Bot responds to /consensus with either consensus output or appropriate error message /consensus generates and displays consensus for active discussion, or shows existing if already generated

Before declaring plan complete: - [ ] `ruff check src/moai/core/orchestrator.py src/moai/core/services/discussion.py src/moai/bot/handlers/` - [ ] `python -c "from moai.core.orchestrator import generate_consensus"` succeeds - [ ] `python -c "from moai.core.services.discussion import save_consensus, get_consensus"` succeeds

<success_criteria>

• generate_consensus() calls AI and returns structured dict
• Consensus persisted to database via save_consensus()
• /consensus command displays formatted consensus
• Help text updated
• No ruff errors </success_criteria>

After completion, create `.planning/phases/06-consensus-export/06-01-SUMMARY.md`