Action Assay is a certification gate for action-labeled robot video: an independent inverse dynamics model reads the actions out of the pixels, and a calibrated gate checks that the video did what its label says. Every episode gets a certificate or a rejection with reasons.
What that took: a 237,422-parameter model trained for 65 cents of GPU time. Held-out action recovery is R² 0.945 on the arms and 0.988 on the grippers, the gate is calibrated on 30 held-out real episodes and 33 faithful re-renders, and in the control battery, shuffled and wrong-arm actions fail hard.
Why certification also gates fixed windows: clip means can hide a local collapse. All seven spliced-action chimeras pass the clip-level check against the render band, and in the four v2 renders the per-frame error after the splice runs 2.0 to 3.3 times the pre-splice level. The clip mean hid it and the per-frame series exposed it, so the gate scores fixed windows as well as the whole clip.
Scope: Action Assay ships as a Python package and an HTTP API, with one reference instrument (bimanual AgileX Piper, 14-D). An instrument is per-embodiment and per-camera-rig, and render bands are additionally per-generator; new embodiments and new generators need their own calibration.