Scanning experiments with Replay Vision

The job: "I'm running an experiment. Watch the recordings and tell me what's actually happening in each variant."

A Replay Vision scanner is a standing LLM probe over session recordings (see [[creating-replay-vision-scanners]] for the general mechanics). The experiment scanner type is built for this job, so use it rather than scoping another type to an experiment:

• The population is the experiment's exposed people, derived server-side from the experiment instead of a hand-built filter.
• Each session's variant comes from the exposure data, never from the model. The model is told what the experiment changes, but not the session's variant, so it describes what the recording shows.
• Variants are sampled evenly, so a 90/10 rollout still gives the small variant enough observations to compare.
• Scanning stops when the experiment ends, and pauses while it is paused.
• Results split by variant with no join: vision-scanners-variants-list and the observations variant filter.

This skill covers what is experiment-specific; the generic create and size mechanics stay in the parent skill.

The flow: resolve the experiment → write the config → size it → create disabled → preview the prompt on a few real sessions → let the user enable it → read the results per variant.

Step 1: Resolve the experiment

experiment-get returns everything needed: the linked feature_flag (its filters.multivariate.variants list is the source of truth for variant keys; parameters.feature_flag_variants can be stale), exposure_criteria, start_date, end_date, and status. If the user didn't identify the experiment, resolve it via [[finding-experiments]] rather than guessing.