experiment

Creates and tracks hypothesis-driven experiments following a lab methodology cycle.

5|Updated Jun 13, 2026
One-click install
npx skills add https://github.com/PatriotAi/ai-lab --skill experiment-patriotai
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: experiment
Source: https://github.com/PatriotAi/ai-lab/tree/main/.claude/skills/experiment
Command: npx skills add https://github.com/PatriotAi/ai-lab --skill experiment-patriotai

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? It turns ad-hoc idea testing into a structured, repeatable process so every hypothesis gets designed, measured, and concluded instead of being forgotten or half-finished. ## Core Features & Use Cases - Structured Experiment Lifecycle: Guides you through hypothesis, success metric, design, launch, measurement, decision, and conclusion steps. - Scaffolded Experiment Folders: Creates an experiments/<slug>/ directory with a README based on the experiment template. - Knowledge Capture: Appends a 3-5 line conclusion to docs/learnings.md and promotes successful experiments into skills/ or automations/. - Use Case: You want to check whether a translation skill speeds up bilingual releases. The Skill creates experiments/translate-uaen-speed/README.md with a hypothesis and metric, then records the measured outcome and final decision. ## Quick Start Ask the assistant to start a new experiment for your hypothesis, for example: start an experiment to test whether the translate-uaen skill speeds up bilingual releases.

Frequently Asked Questions about experiment

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

FAQPage Schema
How do I start a new experiment with this Skill?▼

Say something like "start an experiment" or "let's test a hypothesis" and state your idea. The Skill formulates a hypothesis and success metric, then creates an experiments/<slug>/ folder with a README from the experiment template.

What is the experiment lifecycle this Skill follows?▼

It follows the lab methodology cycle: hypothesis, design, launch, measurement, keep-or-remove decision, and conclusion. Each experiment is a minimal vertical slice, not a full system build.

Where are experiment results and conclusions stored?▼

Results and observations go into the experiment's own README.md inside experiments/<slug>/. A 3-5 line conclusion is always added to docs/learnings.md, even when the experiment is removed.

What happens to a successful experiment?▼

Successful experiments are promoted into the skills/ or automations/ directories. The Skill also updates docs/PLAN.md and the README of the relevant catalog to reflect the promotion.

When should I not use this experiment workflow?▼

Avoid it for large features that cannot be reduced to a single vertical slice, since the methodology enforces one experiment per end-to-end slice. It is also unsuitable for work involving secrets or personal data, which are prohibited in experiment notes.