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measure

Defines UX success metrics, A/B tests, and funnel analysis frameworks.

Updated May 5, 2026
Search Tags:#A/B testing#experimentation#funnel analysis#HEART framework#ux metrics#ethical measurement#goal signal metric
One-click install
npx skills add https://github.com/TheGeekosaurus/blogging-platform-2 --skill measure-thegeekosaurus
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: measure
Source: https://github.com/TheGeekosaurus/blogging-platform-2/tree/main/.agents/skills/measure
Command: npx skills add https://github.com/TheGeekosaurus/blogging-platform-2 --skill measure-thegeekosaurus

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Teams often ship features without knowing whether they worked, or optimize the wrong metrics and end up with dark patterns and misleading dashboards. This Skill connects design decisions to observable evidence by defining what to measure, how to measure it, and how to act on what you learn. ## Core Features & Use Cases - Metric Selection with HEART and GSM: Applies Google's HEART framework (Happiness, Engagement, Adoption, Retention, Task success) and Goal-Signal-Metric mapping to pick the 2-3 dimensions that matter per feature, with counter-metrics for every optimized metric. - A/B Test and Funnel Design: Produces hypothesis structures, minimum detectable effect targets, sample size tables, guardrail metrics, and segmented funnel analyses paired with qualitative research. - Ethical Measurement Review: Detects Goodhart's Law risks and dark metric patterns, pairing every business metric with a user-outcome metric. - Use Case: After launching a new checkout flow, use this Skill to build a GSM chain, design a properly powered A/B test with guardrail metrics, and analyze the funnel drop-offs segmented by device and user type. ## Quick Start Ask the AI to define success metrics and an A/B test plan for your new feature using the measure skill.

Frequently Asked Questions about measure

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I define success metrics for a new UX feature?▼

Use the Goal-Signal-Metric framework: state the user outcome goal, identify the observable behavior signal, then define a quantified metric with formula, data source, and threshold. Select 2-3 HEART dimensions that match the feature's intent rather than measuring everything.

How to design an A/B test with the right sample size?▼

Set the minimum detectable effect before the test, then calculate sample size from baseline conversion rate, MDE, 80% power, and 95% significance. Run at least 1-2 full weekly cycles and define guardrail metrics that must not get worse.

What is the HEART framework for UX metrics?▼

HEART is Google's framework covering Happiness, Engagement, Adoption, Retention, and Task success. Apply it per feature, not globally: a checkout flow emphasizes task success and happiness, while a content feed emphasizes engagement and retention.

When should I not run an A/B test?▼

Skip A/B testing when the required sample size exceeds your monthly traffic, when detecting very small effects on low baseline rates, or when the real problem is structural rather than cosmetic. Use qualitative research instead in these cases.

Why do good metrics sometimes lead to bad product decisions?▼

Goodhart's Law states that when a measure becomes a target it stops being a good measure. Teams incentivized on engagement build infinite scroll and notification spam, so pair every business metric with a user-outcome counter-metric like satisfaction or ease of cancellation.

How do I combine quantitative metrics with qualitative research?▼

Start with quantitative data to identify what and where users struggle, use qualitative research like usability sessions to understand why, then return to quantitative measurement to verify the fix worked. Never make major design decisions from one data type alone.

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