What problem does it solve? Manuscripts submitted to Nature and other high-impact journals are often rejected or delayed because statistical reporting is incomplete, inconsistent, or misaligned with the study design. This Skill audits, rewrites, or drafts Statistical analysis sections, Results text, and figure legends so that sample sizes, replicates, tests, and p values are transparent and reviewer-ready. ## Core Features & Use Cases - Statistical reporting audit: Checks Methods, Results, and figure legends for missing n definitions, undefined error bars, uncorrected multiple comparisons, pseudoreplication, and significance-only language, with P0/P1/P2 severity labels. - Journal-specific checklists: Applies flagship Nature Article requirements (exact n, test tails, ANOVA F/df, t-test t/df, Reporting Summary) and Nature Machine Intelligence legend and source-data rules. - Reviewer-response drafting: Produces point-by-point conservative responses to statistical reviewer comments plus ready-to-paste revised text, flagging unknown facts as AUTHOR_INPUT_NEEDED instead of inventing values. - Use Case: A reviewer says your statistics are insufficient. Paste the reviewer comment, your Statistical analysis paragraph, and figure legends; the Skill returns a risk-ranked issue list, rewritten text, and a draft response letter. ## Quick Start Ask the assistant to check whether your Statistical analysis section and figure legends meet Nature statistical reporting requirements, pasting the manuscript text and noting the target journal.
