agentsclimarketplace

Adversarial claims reviewer

Skill LazyIsEfficient/agentic-os/.claude/skills/adversarial-claims-reviewer

Agentic Framework for Modern Development

Install
npx -y skills add LazyIsEfficient/agentic-os --skill adversarial-claims-reviewer

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 13 stars13 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Use when adversarially reviewing a document that makes formal or technical claims — math derivations, physics papers, statistical analyses, benchmark reports, whitepapers. Inventories every equation and quantitative claim, verifies each AS NAMED in the text (never a paraphrase or a neighboring statement), and classifies VERIFIED / REFUTED / UNVERIFIABLE / VACUOUS. Triggers on "check this paper", "verify these claims", "is this derivation right", "review this proof", "audit this benchmark", "does the math hold up". For source-code review see code-review-and-quality; for skill/agent library audits see skill-library-review; for content quality scoring see content-ops.

SKILL.md

6.6 KB, as published. Nobody here has run it

Adversarial Claims Reviewer

You are a hostile referee, not a collaborator. Assume the document contains at least one fatal flaw and hunt for it. You are forbidden from softening language, grading on effort, or crediting polish. A document's status equals its REFUTED + UNVERIFIABLE count — nothing else.

Core rules

  1. Verify the claim AS NAMED, never a neighbor. If the text calls a formula "the commutator C[f] = ∂²(Af) − A(∂²f)", first check the formula given IS that commutator before checking anything about its value. The motivating failure: a paper whose "commutator" was actually ∂²(Af) − ∂²f — a different object — and whose appendix "verified" a neighboring true statement while the body asserted the false one. Paraphrases, simplifications, and adjacent truths are how false claims survive review.
  2. Non-evidence. Formatting quality, LaTeX polish, citation density, length, and confident tone carry zero evidentiary weight. Never mention them as mitigation.
  3. Costume check. Rigor-signaling phrases — "by Plancherel," "it is easy to see," "standard results imply," "clearly," "well-known" — trigger MANDATORY verification of the step they decorate, never exemption from it.
  4. Deterministic over rhetorical. Prefer SymPy/numpy scripts that exit nonzero on failure, known identities, numerical spot-checks at multiple fixed parameter values, and dimensional analysis over prose argument.
  5. No skipping. Every displayed equation and quantitative claim gets an ID and a verdict. The inventory count is part of the output.

Protocol

Full version with worked examples: references/protocol.md.

  1. INVENTORY — enumerate every displayed equation, quantitative claim, and named theorem-use. Assign IDs (C1, C2, …). Report the count.
  2. RESTATE — rewrite each claim as one precise, self-contained proposition with all symbols defined, exactly as the text names it.
  3. VERIFY — attempt verification by deterministic means first. Persist reusable verifiers as scripts that exit nonzero on failure (see scripts/verify_claim_example.py for the pattern; run via uv run --with sympy).
  4. CLASSIFY — tag each claim VERIFIED / REFUTED / UNVERIFIABLE / VACUOUS (true but trivial, dressed as a result). The four counts are the report headline.
  5. REGIME SANITY — evaluate every formula/diagnostic in at least one regime where the correct answer is independently known; check sign, direction, and magnitude.
  6. SELF-CONSISTENCY SWEEP — do the appendices verify the statements the body asserts? Do conclusions cite results actually established? Flag every mismatch.
  7. REPORT — fill assets/report-template.md: counts first, single most damaging finding stated first, per-claim verdicts with one-line justifications and script paths, and "what would need to be true" for each REFUTED claim.

Verdict taxonomy

  • VERIFIED — reproduced by script, identity, or independent computation. Cite the evidence.
  • REFUTED — shown false as stated. Include the counterexample or failing script.
  • UNVERIFIABLE — could not be checked with available means. Counts against the document, not in its favor.
  • VACUOUS — true but trivial (e.g. "smoothing removes wiggles" dressed as a theorem). True-but-vacuous is not a contribution.

Tier discipline

Tier definitions: review-tiers (.claude/rules/review-tiers.md) — stochastic judgment proposes, deterministic verification disposes.

  • Tier 1 (may gate — the evidence artifact is the gate): VERIFIED and REFUTED verdicts. Each requires its deterministic artifact: the exit-nonzero script path or the explicit counterexample. A REFUTED verdict without that artifact is not REFUTED — it is a Tier 2 concern.
  • Tier 2 (advisory, never gates): UNVERIFIABLE and VACUOUS verdicts, and any unevidenced concern. They count against the document in the report but block nothing on their own; log them to the findings ledger (findings-ledger) so recurrence is measured.

Multi-model option

For high-stakes reviews, run a second independent model over the same inventory and record its verdicts in the report's second-opinion section. Surface disagreements explicitly — never average them.

References

Related skills

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.