From thinking-frameworks-skills
Decomposes North Star metrics into sub-metrics, leading indicators, and causal maps. Use for KPI breakdowns, metric drivers, and experiment prioritization.
How this skill is triggered — by the user, by Claude, or both
Slash command
/thinking-frameworks-skills:metrics-treeThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Copy this checklist and track your progress:
Copy this checklist and track your progress:
Metrics Tree Progress:
- [ ] Step 1: Define North Star metric
- [ ] Step 2: Identify input metrics (L2)
- [ ] Step 3: Map action metrics (L3)
- [ ] Step 4: Select leading indicators
- [ ] Step 5: Prioritize and experiment
- [ ] Step 6: Validate and refine
Step 1: Define North Star metric
Ask user for context if not provided:
Choose North Star using criteria:
See Common Patterns for North Star examples by type.
Step 2: Identify input metrics (L2)
Decompose North Star into 3-5 direct drivers:
See resources/template.md for decomposition frameworks.
Step 3: Map action metrics (L3)
For each input metric, identify specific user behaviors:
If complex, see resources/methodology.md for multi-level hierarchies.
Step 4: Select leading indicators
Identify early signals that predict North Star movement:
Step 5: Prioritize and experiment
Rank opportunities by:
Select 1-3 experiments to test highest-priority hypotheses.
See resources/evaluators/rubric_metrics_tree.json for quality criteria.
Step 6: Validate and refine
Verify metric relationships:
North Star Metrics by Business Model:
Subscription/SaaS:
Marketplace:
E-commerce:
Social/Content:
Decomposition Patterns:
Additive Decomposition:
North Star = Component A + Component B + Component C
Example: WAU = New Users + Retained Users + Resurrected Users
Multiplicative Decomposition:
North Star = Factor A × Factor B × Factor C
Example: Revenue = Users × Conversion Rate × Average Order Value
Funnel Decomposition:
North Star = Step 1 → Step 2 → Step 3 → Final Conversion
Example: Paid Users = Signups × Activation × Trial Start × Trial Convert
Cohort Decomposition:
North Star = Σ (Cohort Size × Retention Rate) across all cohorts
Example: MAU = Sum of retained users from each signup cohort
Avoid Vanity Metrics:
Ensure Causal Clarity:
Limit Tree Depth:
Balance Leading and Lagging:
Avoid Gaming:
Resources:
resources/template.md - Metrics tree structure with decomposition frameworksresources/methodology.md - Advanced techniques for complex metric systemsresources/evaluators/rubric_metrics_tree.json - Quality criteria for metric treesOutput:
metrics-tree.md in current directorySuccess Criteria:
Quick Decision Framework:
Common Mistakes:
npx claudepluginhub lyndonkl/claude --plugin thinking-frameworks-skillsDecomposes top-line metrics into quantified trees with mathematical relationships, sizes nodes, and identifies leverage points for PMs to focus growth efforts.
Builds tailored metrics frameworks for products or businesses, from North Star metric and metric tree to counter-metrics and dashboards. Use for KPI trees, AARRR, HEART, or OKR requests.
Defines North Star Metric and 3-5 input metrics as a constellation. Classifies business game (Attention, Transaction, Productivity) and validates against 7 criteria. For metrics frameworks, key metric selection.