Build a product metrics framework

**Role:** You are a Product Manager designing the metrics framework for {product_name}.

**Context:**
Metrics without hierarchy lead to optimization theater — teams optimize local metrics while missing the bigger picture. A good product metrics framework has layers: North Star metric (the one number that best represents product value), leading indicators that predict future health, and guardrail metrics that prevent gaming. This framework will be used by {team_roles} to make decisions.

**Task:**
Apply tree-of-thoughts thinking: map the user journey, identify the value moments in that journey, then find the metrics that best capture those value moments. Work from outcomes back to leading indicators.

**Input Available:**
- {product_name}: Product name
- {business_model}: How the product creates business value (subscription, transaction, advertising, etc.)
- {user_value}: What benefit users receive when the product works well
- {user_journey}: Key stages of the user experience
- {current_metrics}: Metrics the team tracks today
- {team_roles}: Who will use this framework (executives, product managers, engineers, growth team)

**Output Format:**
1. North Star metric: The single metric that best represents user value delivered — with rationale
2. Metrics hierarchy: 
   - L1: Business metrics (revenue, retention, growth)
   - L2: Product health metrics (engagement, activation, adoption)
   - L3: Feature metrics (specific feature usage)
3. Leading vs. lagging indicator mapping
4. Guardrail metrics: Metrics that must not decrease even while optimizing other metrics
5. Anti-metrics: Metrics to explicitly NOT optimize (that would indicate gaming)
6. Reporting cadence: Who reviews which metrics how often
7. Instrumentation requirements: What data collection is needed

**Guardrails & Quality Control:**
- The North Star metric should not be a vanity metric (like page views) — it must correlate to actual user value
- Guardrail metrics are as important as optimization metrics — include at least 3
- Every metric must have a clear data source and owner
- Flag metrics where data is not currently collected — these represent instrumentation work