moai-domain-ideation

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# Ideation Domain Specialist

Thin orchestrator for the Diverge-Converge ideation pipeline. Delegates creative framework execution to `moai-foundation-thinking` and adds artifact-shaping logic specific to the brain workflow: Lean Canvas section assembly and SPEC Decomposition List extraction.

## Quick Reference

Core responsibilities:
- Phase 2 (Diverge): Generate 5-15 divergent concept angles for the idea
- Phase 4 (Converge): Assemble Lean Canvas into `ideation.md` with all 9 blocks
- Phase 6 (Proposal): Produce `proposal.md` with SPEC Decomposition Candidates section

Key invariants:
- [HARD] SPEC Decomposition Candidates grammar: `- SPEC-{DOMAIN}-{NUM}: {scope}` (see anchor below)
- [HARD] No tech-stack assumptions (language/framework agnostic) in any artifact
- [HARD] Lean Canvas always includes all 9 blocks (missing blocks get placeholder text)
- [HARD] SPEC IDs use generic domain labels (e.g., SPEC-API-001, SPEC-AUTH-001) — never language-specific (e.g., SPEC-FASTAPI-001)

Foundation reuse:
- Diverge step: delegates to `moai-foundation-thinking` modules/diverge-converge.md (Diverge phase)
- Converge step: delegates to `moai-foundation-thinking` modules/diverge-converge.md (Converge phase)
- Critical eval: delegates to `moai-foundation-thinking` modules/critical-evaluation.md

---

## Phase 2: Diverge

### Input

- Clarity-scored idea from Phase 1 Discovery
- User context from AskUserQuestion rounds

### Process

Invoke `moai-foundation-thinking` Diverge-Converge framework (Diverge phase):

1. Generate 5-15 divergent angles for the idea. Each angle explores a different lens:
   - Core feature set angle (minimum viable product)
   - Target user segment angle (niche vs broad market)
   - Distribution channel angle (B2C, B2B, marketplace, API)
   - Revenue model angle (subscription, freemium, per-use, enterprise)
   - Technical differentiation angle (AI, real-time, offline-first, mobile-first)
   - Competitor gap angle (what existing tools fail to do)
   - Adjacent market angle (related problem space)

2. For each angle, produce a one-sentence concept label.

3. Cluster related angles by affinity (max 5 clusters).

### Output

In-memory concept map. NOT persisted to disk at this phase — convergence in Phase 4 determines what is written.

### Language Neutrality Rules

[HARD] During divergence, do NOT anchor any angle to a specific programming language or framework. Describe capabilities, not implementations:
- Correct: "real-time collaborative editing engine"
- Wrong: "Node.js WebSocket server with React frontend"

---

## Phase 4: Converge — Lean Canvas Assembly

### Input

- Phase 2 diverged concept map
- User's original idea
- Optional: brand context from `.moai/project/brand/brand-voice.md`

### Process

Invoke `moai-foundation-thinking` Diverge-Converge framework (Converge phase) to reduce 5-15 angles to the single most defensible product concept.

Then assemble the Lean Canvas.

### Lean Canvas — 9 Blocks

Populate each block for the converged concept. Every block MUST be present, even if sparse. Empty blocks get placeholder: `[TBD — to be refined with user research]`.

```
## Lean Canvas

### Problem
[Top 3 problems this product solves for the target customer]

### Customer Segments
[Specific user personas — who has the problem most acutely?]

### Unique Value Proposition
[Single, clear, compelling message — why this over alternatives]

### Solution
[Top 3 features / capabilities that address the problems]

### Channels
[How the product reaches customers: direct, marketplace, viral, partnerships]

### Revenue Streams
[How value is monetized: subscription, freemium, per-use, enterprise license, API]

### Cost Structure
[Main cost drivers: infrastructure, people, acquisition, support]

### Key Metrics
[The numbers that tell you the product is succeeding — leading and lagging indicators]

### Unfair Advantage
[What is genuinely hard for competitors to copy? Network effect, data, brand, IP, team]
```

### Language Neutrality in Solution Block

[HARD] The Solution block describes WHAT the product does, not HOW it is built:
- Correct: "High-throughput transformation engine that processes 10K events/sec"
- Wrong: "Python Pandas pipeline running on Airflow DAGs"

### Output

Write `ideation.md` to `.moai/brain/IDEA-NNN/`:

```markdown
# Idea: {user's original idea, verbatim}
*Session: {date}*

## Lean Canvas

[9 blocks as specified above]

```

---

## Phase 5 Append: Critical Evaluation

After Phase 5 executes (managed by `moai-foundation-thinking` critical-evaluation.md), append the evaluation report to the existing `ideation.md`:

```markdown
## Evaluation Report

### Strengths
[Evidence-backed strengths from critical evaluation]

### Weaknesses
[Identified gaps, assumptions, and risks]

### First Principles Validation
[First principles breakdown per moai-foundation-thinking/modules/first-principles.md]

### Verdict
[Proceed / Proceed with caveats / Revisit / Abandon — with rationale]
```

---

## Phase 6: Proposal — SPEC Decomposition List

### Input

- `ideation.md` with Lean Canvas + Evaluation Report
- User's confirmation to proceed

### Process

Translate the converged product concept into actionable SPEC candidates. Each candidate represents a discrete, independently-implementable unit of work.

#### SPEC ID Naming Convention

[HARD] SPEC domain labels MUST be generic capability terms, never technology/language names:

| Correct (capability-based) | Wrong (technology-based) |
|------------------