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.