Audit and edit an ML/AI paper draft for internal consistency after sections exist. Use when the user wants title, abstract, introduction, method, experiments, figures, tables, captions, claims, terminology, limitations, and conclusion to tell the same story without acting as a hostile reviewer.
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Install skill "paper-draft-consistency-editor" with this command: npx skills add a-green-hand-jack/skillsmp-a-green-hand-jack-a-green-hand-jack-paper-draft-consistency-editor
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Plan, draft, and revise ML/AI limitations, scope, failure cases, ethics, broader impact, and conclusion caveats so they control claim boundaries without undermining the paper. Use when the user wants limitation wording, scope statements, failure-case interpretation, ethics/broader-impact text, or overclaim reduction.
Plan, draft, and revise ML/AI method sections for clarity, notation flow, module ordering, algorithm boxes, overview figures, design rationales, and appendix boundaries. Use when the method exists but needs to be explained clearly in paper prose.
Turn ML/AI experiment tables, figures, ablations, and metrics into claim-aware results prose. Use when the user wants experiment section structure, result paragraph openings, table/figure narrative, ablation interpretation, mixed-result wording, provisional result placeholders, or evidence-to-claim storytelling.
Draft and revise ML/AI paper titles, abstracts, and contribution lists so the paper's highest-level promise matches its venue, positioning, claims, and evidence. Use when the user wants title options, abstract structure, contribution bullets, claim-strength calibration, or title/abstract/contribution consistency.