calibration_labels.json — per-frame color labels. Used by atm validate-calibration to check the current palette classifies known-good dots correctly before a live session.
scenarios.json — ordered frame sequences per FSM scenario (full cycle, phase skip, catchup, post-fire suppression). Consumed by tests/test_scenarios_regression.py which runs each sequence through the full Detector → _handle_tick pipeline and asserts color, FSM reason/state, emitted alerts, and scheduler on/off.

Frames live in calibration/frames/ and are self-contained: purging logs/fires/ or samples/ does not break either artifact.

calibration_labels.json schema

Schema

A JSON array of entries. Each entry:

Field	Type	Required	Description
`path`	string	yes	Path to a PNG frame (relative to CWD or absolute).
`expected`	string	yes	Expected color name: one of `turquoise`, `yellow`, `dark_green`, `dark_red`, `light_green`, `light_red`, `gray`.
`note`	string	no	Freeform annotation; shown in SUGGESTIONS output.

atm validate-calibration calibration/calibration_labels.json

Exit codes:

Find a screenshot in logs/fires/ whose dot color you can verify by eye.
Copy it into calibration/frames/ — this directory is self-contained so logs/fires/ and samples/ can be emptied without breaking validation.
Append an entry with path (pointing to calibration/frames/...), expected, and an optional note.
Re-run validation. If it FAILs, the SUGGESTIONS section will tell you the RGB distance between the observed pixel and the expected color's center — use that as input for atm calibrate.