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brainstorm-experiments-existing

Design low-effort experiments to validate product assumptions for existing products.

1|Updated May 6, 2026
Search Tags:#product management#experiment design#product discovery#a/b testing#assumption validation#prototype testing#fake door test
One-click install
npx skills add https://github.com/moonzff/Codex_up --skill brainstorm-experiments-existing-moonzff
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: brainstorm-experiments-existing
Source: https://github.com/moonzff/Codex_up/tree/main/skills/metrics-experiments/brainstorm-experiments-existing
Command: npx skills add https://github.com/moonzff/Codex_up --skill brainstorm-experiments-existing-moonzff

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Product teams often commit to building features based on untested assumptions, wasting engineering effort on ideas users do not want. This Skill helps you design cheap, fast experiments to validate assumptions before full implementation. ## Core Features & Use Cases - Assumption Clarification: Confirms what the team wants to build and which beliefs need validation before any experiment is designed. - Experiment Design: Suggests validation methods such as first-click testing, fake door tests, technical spikes, A/B tests, Wizard of Oz approaches, and behavioral surveys. - Structured Output: Produces each experiment with a defined assumption, method, metric, and success threshold in a clear table or markdown format. - Use Case: A product manager has a new onboarding feature idea. Use this Skill to generate a fake door test measuring click-through rate, with a success threshold that decides whether to proceed with development. ## Quick Start Ask the assistant to design low-effort experiments that validate the assumptions behind your feature idea, describing your product context and what you believe to be true.

Frequently Asked Questions about brainstorm-experiments-existing

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

FAQPage Schema
How do I validate product assumptions before building a feature?▼

Design low-effort experiments such as fake door tests, prototypes, or technical spikes that measure actual user behavior rather than opinions. Define the assumption, the experiment, the metric, and a success threshold before running anything.

What experiments can test a feature idea cheaply?▼

Common low-cost methods include first-click testing with prototypes, feature stubs or fake doors, Wizard of Oz approaches, and behavioral surveys. Each method trades fidelity for speed, so match the method to the risk of the assumption.

How do I run an A/B test on production safely?▼

Limit exposure to a small user segment, define rollback criteria in advance, and monitor guardrail metrics alongside the primary metric. The Skill requires explicit risk mitigation strategies for any production experiment.

Why should I measure behavior instead of user opinions?▼

Stated opinions in surveys often diverge from real usage, so behavioral metrics like clicks, task completion, and conversion give more reliable validation. Opinion-based surveys should only supplement behavioral evidence.

When should I not run a product experiment?▼

Avoid experiments that put users or the business at risk, such as tests touching payments, privacy, or legal compliance without safeguards. In those cases use lower-risk methods like technical spikes or internal reviews.

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