paper-claim-auditor

name	paper-claim-auditor
description	Use when auditing a CFD-AI/SciML manuscript's abstract, introduction, contributions, or discussion to verify that every claim is supported by evidence and scoped correctly.
version	0.3.0
author	CFD-AI Paper Skills maintainers
metadata	{"short-description":"Claim-evidence audit for CFD-AI/SciML papers"}

Paper Claim Auditor

Trigger

Use when asked to avoid overclaiming, check novelty, audit abstract/introduction/conclusion, or map claims to evidence.

Progressive disclosure

• Read rubrics/claim-evidence-rubric.md before scoring.
• Route to skills/reviewer-audit-toolkit/SKILL.md when the user asks for a gate decision, rejection risk, submission readiness, or minimum rescue plan.
• Read rubrics/vocabulary-style-rubric.md when the text contains loaded adjectives such as robust, generalizable, physically consistent, novel, state-of-the-art, interpretable, efficient, real-time, promising, or transformative.
• Use references/field-terminology-style-guide.md to replace AI-ish prose with field-native CFD-AI/SciML wording.
• Use references/gold-paper-style-patterns.md and rubrics/gold-paper-closeness-rubric.md when text sounds fluent but unlike a normal CFD-AI/SciML paper.
• Use templates/claim-evidence-map.md for full audits.
• Use examples/bad-to-good-abstract.md, examples/ai-ish-to-field-native-prose.md, and examples/generic-ai-to-gold-paper-prose.md when rewriting abstracts or conclusions.
• Read gold-paper files only when the claim domain matches:
  • reconstruction: references/gold-papers/fukami-2019-super-resolution-jfm.md
  • field taxonomy: references/gold-papers/brunton-2020-machine-learning-fluid-mechanics.md
  • uncertainty/trust: references/gold-papers/maulik-2020-probabilistic-neural-networks-prf.md
  • wake prediction: references/gold-papers/lee-2019-cylinder-wake-jfm.md
  • CFD opportunity framing: references/gold-papers/vinuesa-2022-enhancing-cfd-ml.md

Workflow

1. Extract all major claims.
2. Classify claim type: novelty, accuracy, physical consistency, generalization, robustness, efficiency, interpretability, reproducibility.
3. Map each claim to evidence location.
4. Score evidence strength: supported / weak / missing / overclaimed.
5. If the paragraph is generic or AI-ish, score gold-paper closeness: physical anchoring, rhetorical move order, field-native collocations, and limitation boundary.
6. Suggest safer wording or required experiment.

Output schema

Claim	Type	Evidence location	Status	Risk	Fix

Add a rubric score:

Claim	Score 0-3	Missing evidence	Safer wording

For prose-style audits, add:

Passage	Gold-paper closeness score 0-3	AI-ish marker	Field-native rewrite

Anti-patterns

• “robust” without robustness tests.
• “generalizable” from random split only.
• “physics-informed” without locating physics in loss/architecture/data/constraints.
• “state-of-the-art” without fair baselines.
• “real-time” without hardware/runtime.
• “AI framework” or “complex dynamics” where the paper should name input, output, flow regime, metric, and diagnostic.
• Generic context paragraphs that do not mention a physical object by the third sentence.

Verification

• Every claim has evidence or TODO.
• No solver/citation details invented.
• Safer wording preserves contribution without hype.
• Claims scored 0-1 are either removed, narrowed, or converted to explicit TODOs.
• Gold-paper closeness failures are rewritten using examples/generic-ai-to-gold-paper-prose.md.