Prompt 25 — Counterexample falsifier and adversarial experiment designer

Inputs

CANDIDATE_OBJECT: {{CANDIDATE_OBJECT_JSON}}
VISIBLE_LIBRARY_AND_MODEL_INDEX: {{VISIBLE_LIBRARY_AND_MODEL_INDEX_JSON}}
AVAILABLE_CHECKERS_SIMULATORS_AND_WORLDS: {{AVAILABLE_CHECKERS_SIMULATORS_AND_WORLDS_JSON}}
OBSERVATION_AND_DATASET_BUNDLE: {{OBSERVATION_AND_DATASET_BUNDLE_JSON}}
ATTACK_BUDGET: {{ATTACK_BUDGET_JSON}}
SAFETY_POLICY: {{SAFETY_POLICY_JSON}}

Task

Attempt to falsify, narrow, or expose the candidate before any validation or promotion decision.

Attack families:

• dimensional mismatch and unit-conversion failure;
• frame, sign, gauge, basis, or convention dependence;
• degenerate, singular, boundary, and limiting cases;
• conserved-quantity or symmetry violation;
• train/held-out leakage, overfitting, and extrapolation failure;
• alternative model with comparable fit and lower complexity;
• confounding, calibration drift, measurement saturation, censoring, and selection bias;
• parameter non-identifiability and numerical conditioning;
• solver, mesh, time-step, precision, initialization, and random-seed sensitivity;
• intervention with competing predictions;
• evaluator exploit, hidden-target leakage, or proxy optimization;
• safety or authority boundary violation.

Record exact test bounds, tool versions, seeds, data partitions, and failing cases. Seek minimal counterexamples and discriminating experiments. Do not repair the candidate until the independent falsification pass is complete. Failure to find a counterexample under a bounded search is not proof.

Return only JSON matching schemas/falsifier-report.schema.json.