Diagnose growth loops and design experiments for activation, retention, and referral.
npx skills add https://github.com/felixgeelhaar/skills --skill growth-expert
Please help me install this Agent Skill. Skill: growth-expert Source: https://github.com/felixgeelhaar/skills/tree/main/growth-expert Command: npx skills add https://github.com/felixgeelhaar/skills --skill growth-expert
Growth teams often struggle to identify where to intervene to unlock compounding growth. This Skill provides a structured framework to design, diagnose, and optimize growth loops, activation, retention, and monetization with rigorous experimentation.
Map your current activation bottleneck and draft one hypothesis to improve it within the next sprint.
High-intent search queries and answers about installing and using this skill.
To design growth loops, you must diagnose activation and retention bottlenecks, frame structured hypotheses, and run experiments to optimize user onboarding. This framework provides a methodology to map, diagnose, and optimize compounding growth loops based on established PLG principles.
The best way to structure product growth experiments involves rigorous hypothesis framing, OEC selection, power analysis, and establishing clear decision rules. This approach ensures data-driven interventions across acquisition, engagement, and monetization loops for product-led growth.
Yes, you can optimize onboarding and activation for non-PLG products. The framework applies to product-led growth as well as non-PLG scenarios, offering on-demand coaching across acquisition, engagement, and monetization loops.
Identifying activation funnel bottlenecks requires an activation-first mindset to analyze user drop-offs and propose data-driven interventions. This methodology helps isolate specific onboarding friction points to target with structured growth experiments.
You should involve cross-functional experts in growth experimentation when diagnosing complex loops that span product, data, UX, or finance domains. The framework supports pairing capabilities to defer to specialized experts for handling cross-domain questions.
Retention loops fail to compound user growth when bottlenecks in activation and expansion prevent sustained engagement. Diagnosing these loops with a rigorous experimentation framework helps identify missing referral mechanics or data-driven intervention opportunities.
dtsongDesign growth engineering infrastructure for onboarding funnels, referral systems, and A/B testing.
TravisLeeeeeeDesign, track, and analyze A/B experiments with statistical rigor.
OneWave-AIAssemble 2-3 expert personas to collaboratively analyze any topic.
Nir-BhayDesign and analyze A/B tests for growth experiments using Python, SQL, and YAML.
