executing-plans
executing-plans
Use when executing an implementation plan in the current session as the implementer yourself — your human partner chose inline execution, or no subagent tool is available
jailbreak_proxy_evaluatorCompute held-out benign-versus-adversarial obedience deltas and mechanism checks for safe jailbreak proxies.
Independent GitHub snapshot · Automated classification · Original documentation governs
Use this skill to evaluate whether an optimized visual prompt changes held-out behavior in a safe proxy experiment. It mirrors the paper's comparison between benign image and adversarial image conditions without generating or scoring harmful text.
target: metadata from module_plan.json.fast_recovery_target.protocol: output from the safe corpus protocol skill.benign_scores: prompt IDs mapped to numeric baseline scores.adversarial_scores: prompt IDs mapped to numeric optimized-prompt scores.metrics.obedience_delta: mean adversarial score minus mean benign score.category_metrics: optional per-category means and deltas.mechanism_checks: booleans for held-out split validity, prompt change, loss decrease, target match, and threshold success.obedience_delta for the proxy recovery.Run:
python scripts/proxy_evaluator.py --self-test
The tests cover metric calculation, category aggregation, and missing-score rejection.
This evaluator cannot establish real-world jailbreak harm. It validates a mechanism-faithful, harmless proxy under soft-mode constraints.