Returns one entry per run with its experiment_id, the constraint, dataset,
seed and logic it used, and how many epochs it recorded. Call this first:
every other experiment tool takes an experiment_id that comes from here.
The constraint filter accepts either the class name (StandardRobustness)
or the folder name that appears in ids (standard-robustness).

Returns only the config keys that differ, plus deltas on predictive
performance and constraint security. Prefer this over calling get_results
twice when the question is what changed between two runs.

With dry_run=true (the default) it validates every argument, returns the
exact command, and touches nothing. Do that first and show the plan.

With dry_run=false it executes, subject to two independent gates: the
operator must approve the exact call, and the server must have been
started with execution enabled. If either refuses, the result says
status refused or declined_by_operator. Do not retry a refused or
declined call; report it. A completed run returns the experiment_id to
pass to get_results. Training takes minutes even for one epoch;
oracle_steps and oracle_restarts control the adversarial attack cost.