Adversarial Verify

Adversarial verification

1. Read the UTF-8 target claim, its complete dependencies, linked evidence, and project policy from disk. Do not rely on a prior conversational summary. On Windows, use an explicitly UTF-8-safe reader.
2. Confirm the verifier is not listed as an author. Stop if independence cannot be established.
3. Reply in the explicit or configured language: English, Traditional Chinese, Simplified Chinese, or Japanese. Preserve the original claim and evidence text.
4. Attack the claim before accepting it:
   • formal: check hypotheses, implication direction, boundary cases, asymptotics, and every proof step;
   • literature: open the source and verify the exact locator and support scope;
   • empirical: reproduce or inspect the dataset, computation, uncertainty, and limitations;
   • benchmark: check data, environment, metric definition, baseline, and reproducibility;
   • synthesis: verify every dependency is currently VERIFIED. For imported evidence bundles, inspect the preserved result, profile, scope, and artifact digests. Treat producer-supplied hashes as integrity records, not independent reproduction or proof of runner identity.
5. Choose exactly one outcome: ACCEPT, REJECT, or UNCERTAIN. Absence of a found counterexample is not proof.
6. For a PROPOSED or UNDER_REVIEW claim, write a verification request with rationale and checked evidence IDs, then run rigorgraph verify CLAIM_ID --file REQUEST.json.
7. For an already VERIFIED claim whose support fails, do not overwrite history or try to verify it again. Report a release-blocking revocation recommendation and the decisive issue codes.
8. Run rigorgraph audit and report the outcome plus any remaining audit issues. If rigorgraph is not on PATH, use python -m rigorgraph or the project virtual-environment executable.

Use localized headings:

VERIFIED means accepted by this recorded workflow; it does not mean absolute truth, formal certification, or peer review.