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experiment

Plan Bottie strategy changes as controlled experiments with hypotheses and success criteria.

Updated Aug 23, 2026
Search Tags:#statistics#data-analysis#baseline#experiment#sample-size#go-no-go#bottie
One-click install
npx skills add https://github.com/Liquilab/Bottie --skill experiment-liquilab
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: experiment
Source: https://github.com/Liquilab/Bottie/tree/main/.claude/skills/experiment
Command: npx skills add https://github.com/Liquilab/Bottie --skill experiment-liquilab

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Rigorous, data-driven design and tracking of Bottie strategy changes to ensure disciplined experimentation and evidence-based decisions.

Core Features & Use Cases

  • Define hypotheses, baselines, and success criteria for each Bottie strategy change.
  • Compute required sample sizes, monitor ongoing experiments, and record results in data/experiments.
  • Enable clean Go/No-Go decisions with documented outcomes and guardrails, all anchored to VPS data.

Quick Start

Design a new Bottie experiment by issuing /experiment nieuw "description" and monitor progress with /experiment status or /experiment check [name].

Frequently Asked Questions about experiment

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

FAQPage Schema
How do I design a controlled experiment for Bottie strategy changes?▼

To design a controlled experiment for Bottie strategy changes, define a formal hypothesis, establish a baseline from VPS data, and set clear success criteria. You can initialize this structured experiment design using the /experiment command.

What is the best way to calculate sample size for data analysis experiments?▼

Calculating sample size for data analysis experiments involves applying statistical formulas to your VPS baseline data to ensure results are significant. This Skill computes the required sample size to help you monitor ongoing experiments accurately.

How do I make Go/No-Go decisions based on baseline data and statistics?▼

Making Go/No-Go decisions based on baseline data requires comparing ongoing experiment results against predefined success criteria and guardrails. This process yields documented outcomes anchored to your VPS data to finalize the decision.

Can I track ongoing experiment status and documented results in data/experiments?▼

Yes, you can track ongoing experiment status and documented results in data/experiments by using the /experiment status or /experiment check commands. This monitors data collection and records outcomes for your Bottie strategy tests.

Do I need VPS data to measure baseline and success criteria for an experiment?▼

Yes, you need VPS data to measure the baseline and evaluate success criteria for an experiment. The data anchors the hypothesis testing, sample size calculation, and final documented results required for disciplined experimentation.

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