Define a north star metric and KPIs with SQL definitions and data dictionary entries.
npx skills add https://github.com/tonone-ai/tonone --skill lens-metrics
Please help me install this Agent Skill. Skill: lens-metrics Source: https://github.com/tonone-ai/tonone/tree/main/team/lens/skills/lens-metrics Command: npx skills add https://github.com/tonone-ai/tonone --skill lens-metrics
Product teams often lack a precise, agreed-upon set of metrics. This Skill defines a north star, supporting KPIs, and operational metrics with exact definitions and SQL queries to ensure trust and alignment across stakeholders.
Define your product's north star metric and associated KPIs, then implement SQL views to track them.
High-intent search queries and answers about installing and using this skill.
Defining a north star metric requires establishing a precise, time-bound measure of product value alongside 3-5 supporting KPIs with exact definitions, targets, and ownership to ensure stakeholder alignment.
Creating SQL definitions for a metrics data dictionary involves writing tested SQL queries for your north star and operational metrics, then documenting them in a metrics file to maintain trust and operability.
To explain north star movement, you need operational metrics covering funnel, engagement, quality, and efficiency, each with explicit definitions and tested SQL queries to capture product performance accurately.
Yes, this metrics framework aligns with dbt by implementing metric definitions as SQL views and documenting them within a data dictionary file to govern metrics end-to-end.
The best way to govern product metrics is to define a comprehensive framework with a north star metric, supporting KPIs with explicit owners, and tested SQL views documented in a data dictionary for trust.
Product teams need a metrics framework with explicit definitions and ownership because lacking agreed-upon metrics causes misalignment, making precise definitions and documented ownership essential for stakeholder trust.
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