git:20260812.24c2477 to git:20260914.d73e4dd

---

name: wicked-garden-product-synthesize

description: |

Generate actionable recommendations from customer voice insights. This skill

should be used when the user needs to translate analyzed feedback into product

priorities, feature recommendations, or strategic guidance.

Use when: "recommendations from feedback", "translate feedback to priorities",

"feature priorities from customer data", "synthesize feedback into action"

---

# Synthesize Skill

Transform customer voice analysis into actionable product recommendations.

> Tier-3 knowledge module behind the **`synthesize`** action of the

> `wicked-garden-product` domain skill (`skills/product/SKILL.md`). Canonical

> invocation: `/wicked-garden-product synthesize [args]` or plain natural

> language — the examples below use that form.

## When to Use

- After analyzing customer feedback

- Product planning or roadmap prioritization

- Feature decision support

- User asks "what should we build based on customer feedback"

## Usage

```bash

# Synthesize all recent insights

/wicked-garden-product synthesize

# Prioritize by impact level

/wicked-garden-product synthesize --priority high

# Feature-specific synthesis

/wicked-garden-product synthesize --feature "mobile-app"

# Brief format (for quick decisions)

/wicked-garden-product synthesize --format brief

```

## Synthesis Framework

### 1. Insight Extraction

Identify: Pain Points, Opportunities, Risks, Strengths

### 2. Recommendation Generation

Score = (Customer_Value × Urgency) / Effort

See [refs/prioritization.md](refs/prioritization.md) for detailed scoring.

### 3. Customer Journey Mapping

Map feedback across: Awareness → Evaluation → Onboarding → Adoption → Retention → Advocacy

See [refs/journey-mapping.md](refs/journey-mapping.md) for stage analysis.

### 4. Priority Levels

- **P0**: Churn risk, blocker, security

- **P1**: Major friction, competitive gap

- **P2**: Enhancement, efficiency

- **P3**: Nice-to-have, edge case

## Output Format

```markdown

## Customer Voice Synthesis: {Context}

### Executive Summary

{2-3 sentences on what customers need most}

### Top Recommendations

1. **{Recommendation}** - {Priority}

- Impact: {HIGH/MEDIUM/LOW}

- Evidence: {N} mentions, {sentiment}, {trend}

- Action: {specific what to do}

- Effort: {LOW/MEDIUM/HIGH}

{Top 3-5 recommendations}

### Customer Journey Insights

- **Onboarding**: {key pain point or win}

- **Adoption**: {key pain point or win}

- **Retention**: {key pain point or win}

### Strategic Considerations

- **Strengths**: {what to maintain}

- **Risks**: {what threatens retention}

- **Opportunities**: {what could differentiate}

### Quick Wins

{1-3 low-effort, high-impact improvements}

### Long-term Bets

{1-2 strategic investments based on customer needs}

```

## Synthesis Process

1. Load theme and sentiment analysis from the product voice analysis directory (resolved via `resolve_path.py wicked-garden:product`)

2. Sort themes by priority score, filter by threshold

3. Generate recommendations: theme → action, score by impact/effort

4. Map to customer journey stages, identify friction points

5. Format output: executive summary first, top 3-5 recommendations

## Integration

**wicked-crew**: Auto-inject synthesis into `product:requirements:started` events

**wicked-garden-mem (store action)**: Store high-priority insights as decision memories

**Native tasks**: Link recommendations to roadmap tasks via TaskCreate with `metadata.event_type="task"`

## Rules

- Maximum 5 recommendations (context efficiency)

- Always include effort estimates

- Provide confidence levels (HIGH/MEDIUM/LOW)

- Cite supporting evidence (N mentions, sentiment)

- Distinguish quick wins from strategic bets

- Keep output under 1000 words

- Be honest about unknowns and limitations