modeling-activation-metrics

modeling-activation-metrics is a Product analytics & metrics skill for AI agents, published by PostHog in the posthog.com repository on GitHub. Skillspace rates modeling-activation-metrics D (62/100) and it passed the safety scan; the rating is based on static analysis only.

Build reusable activation models — an activation-rate metric and a per-user/per-account activated flag — on either PostHog data-warehouse views (HogQL) or an external dbt project. Use when the user wants to define, model, or measure activation, the "aha moment", onboarding success, or which early actions predict a user sticking around. The core idea this skill enforces: activation is NOT a single assumed event — it is a retention-validated combination of early actions, chosen by balancing reach (enough users hit it) against predictive power (those who hit it retain much better). Covers finding candidate actions, validating them against retention lift, count thresholds and action combinations, per-product and B2B group-level activation, and modeling the winning definition as a durable activated-flag + activation-rate model. Read modeling-warehouse-foundations first; composes modeling-product-usage-metrics for the retention validation.

Grade
D
Quality
62 / 100
Safety
Passed
GitHub stars
1,138

Unproven: rated by static analysis only, not yet compared head-to-head.

Our two independent classifiers differ on this skill's category, so treat the placement as provisional.

This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.

Our review

Architecture
78 / 100
Maturity
Structured: ships references or scripts
Security scan
No issues found
License
Not declared. Check the repository before reusing it.

Not checked yet

  • Category is a classifier prediction; no model has read this skill yet
  • Not judged on the rubric yet (not a contender in its category)
  • No blind task eval yet
  • Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
  • Sibling files (scripts, references) not fetched; security scan covers SKILL.md only

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