Product tracking model
Skill yigityildiz0/universal-ai-skill-library/skills/common/product-tracking-model
Model a product before telemetry work by defining users, value moments, entities, lifecycle states, and decision questions. Use when asked to map a product for analytics, define what a product does, prepare a tracking model, or establish a telemetry foundation.From its SKILL.md
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SKILL.md
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Product Tracking: Model
Create a compact product model that makes later telemetry decisions traceable. Do not select an analytics vendor, add SDKs, or send data.
Workflow
- Read only the product materials and repository areas the user put in scope.
- Separate confirmed facts from assumptions. Ask only for facts that materially change the model.
- Define:
- primary user roles and accountable organizations;
- the smallest meaningful value moment;
- core entities and their stable relationships;
- lifecycle states, permissions, and meaningful transitions;
- product questions that evidence should answer.
- Identify sensitive fields. Prefer pseudonymous identifiers and data minimization; do not include secrets, free-form user content, regulated data, or unnecessary identifiers in telemetry.
- Produce a reviewable model before designing events.
Deliverable
Use this structure in conversation or, when the user requests project artifacts, propose .telemetry/product-model.md:
Product outcome
Users and organizations
Core value moment
Entities and relationships
Lifecycle states and transitions
Decision questions
Known unknowns and privacy boundaries
Quality bar
- Every proposed event later must map to a decision question or value moment.
- Do not turn every click into a product event.
- Mark inference clearly; never pretend a codebase proves product intent.
- Hand off to
product-tracking-auditfor current reality orproduct-tracking-planfor the target design.
What ships with it
Read from the repository
Just SKILL.md. No reference files, no scripts.