nature-statistics

Audit and rewrite statistical reporting text for Nature-style journal manuscripts.

2|Updated Jun 18, 2026
One-click install
npx skills add https://github.com/AlexenderSokolov/deepscientist-lite-codex-plugin --skill nature-statistics-alexendersokolov
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: nature-statistics
Source: https://github.com/AlexenderSokolov/deepscientist-lite-codex-plugin/tree/main/plugins/deepscientist-lite-academic/skills/nature-statistics
Command: npx skills add https://github.com/AlexenderSokolov/deepscientist-lite-codex-plugin --skill nature-statistics-alexendersokolov

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve? Manuscript statistics sections often hide pseudoreplication, undefined error bars, uncorrected multiple comparisons, or significance-only claims that trigger reviewer rejection. This Skill audits, rewrites, or drafts statistical reporting so Methods, Results, and figure legends are transparent, reproducible, and aligned with the actual study design. ## Core Features & Use Cases - Statistical Reporting Audit: Classifies issues by severity (P0/P1/P2), detecting pseudoreplication, wrong interaction inference, analysis-unit mismatch, and uncorrected multiple comparisons. - Ready-to-Paste Rewrites: Produces conservative Statistical analysis paragraphs, Results wording, and figure-legend text with explicit n definitions, test names, and correction strategies. - Reviewer Response Support: Drafts point-by-point responses to statistical reviewer comments and generates AUTHOR_INPUT_NEEDED checklists for missing design facts. - Use Case: A reviewer says your statistics are insufficient because n counts cells rather than animals. Use this Skill to identify the independent experimental unit, rewrite the legend with panel-specific n and exact p values, and draft a conservative response letter. ## Quick Start Ask the assistant to review the Statistical analysis section and figure legends of your manuscript for Nature-style reporting issues and produce a revised draft.

Frequently Asked Questions about nature-statistics

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I check if my Statistical analysis section meets Nature reporting standards?▼

Submit your Methods or Statistical analysis text for a bounded audit that maps each claim to its test, assumptions, sample size, and correction strategy. The review returns severity-labeled issues (P0/P1/P2) plus ready-to-paste revised wording.

How should I write error bars, n, and p values in figure legends?▼

Each quantitative panel legend should define what n represents, the summary convention (mean ± s.d., s.e.m., or CI), the test used, and exact p values or defined star thresholds. The figure-statistics reference checks bar plots, box plots, violins, time courses, and heat maps against these requirements.

What is pseudoreplication and how do I avoid it in my manuscript?▼

Pseudoreplication occurs when cells, images, fields, or technical wells are counted as independent n instead of the true experimental unit such as animals, donors, or cultures. The fix is to analyze independent units, aggregate technical subsamples, or use hierarchical mixed-effects models.

Can this skill reanalyze my raw data or choose a statistical test for me?▼

It is a reporting and review skill, not a substitute for a statistician. It only performs concrete reanalysis when you supply the raw data and explicitly request computation, and it will not recommend a final test when the unit of analysis or design is unclear.

How do I respond to reviewer comments saying my statistics are insufficient?▼

Provide the reviewer comments and your current text to get a structured response draft covering the concern, the author-side action needed, and revised manuscript wording. It never claims a new analysis was performed unless you supply the results.

What are the limitations of automated statistical reporting review?▼

The review cannot infer experimental units or independent replicates from figures alone and cannot verify facts not present in the supplied material. Missing sample sizes, tests, or design details are flagged as AUTHOR_INPUT_NEEDED rather than guessed.