Reward Seeking Evidence Review

Review evidence and calibrate claims about reward-seeking, reward hacking, grader targeting, evaluation gaming, or oversight-dependent behavior. Use before saying a model is safe, aligned, deceptive, reward-seeking, or improved; also use to distinguish executed behavior, code-path evidence, assumptions, and inconclusive null results.

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Reward-Seeking Evidence Review

Build a claim ledger:

Claim Distribution Evidence Status Does not establish

Tag status as executed, code_path, inferred, or assumed. A passing unit test for an evaluator proves evaluator plumbing, not model behavior. A behavioral shift proves sensitivity in that condition, not a stable global objective.

Check:

  • model/provider/version and harness version are pinned;
  • task distribution, authority pair, prompt channel, tool policy, and date exist;
  • positive and negative controls worked;
  • feature opportunity, invalids, refusals, and uncertainty are reported;
  • final actions and receipts support the claim independently of chain-of-thought;
  • a null is not caused by failed activation or low power;
  • the result replicated on a changed surface form;
  • an independent decision-maker, not the evaluated grader alone, owns release.

Rank the strongest defensible claim first. Downgrade overbroad language and state the exact next experiment needed to close each gap.

jpoindexter/reward-seeking-safety-skills/tree/main/skills/reward-seeking-evidence-review commit 2c7e1a8091

Frequently asked questions

npx skillmds@latest add jpoindexter/reward-seeking-evidence-review