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env run

Executes a project’s mission phase-by-phase, logging every tick and running the LLM judge at the end for a verdict.
env run requires the gym extra (MuJoCo). Install with pip install -e ".[gym]".

Flags

Output

Each run writes two files under <project>/.cadenza-env/: The scripted driver exercises the full loop and emits fine-tune records but is not a learned policy. To drive the same mission with your own model, see Custom environments.

env stats

Aggregate motion and reward analytics across a project’s cached runs.
Reports per-phase success, reward breakdowns, and motion summaries, so you can see whether edits to your reward shaping or policy actually helped.

env cache

Show or prune the per-project .cadenza-env/ run directory to manage disk.