Audit Manuscript Stats with a Nature-Ready Agent Skill

Where this fits

A postdoc sends you a draft with p-values scattered across Results and a figure legend that says "n=3" without clarifying biological vs. technical replicates. They ask: "Can you check the statistics before we submit to Nature?" You need to verify reporting transparency, not redo the analysis. This skill gives your agent a structured checklist for exactly that scenario.

Why agents benefit

• Parses statistical claims: Extracts and evaluates p-values, confidence intervals, effect sizes, and sample sizes from text, flagging missing or inconsistent reporting.
• Separates design layers: Distinguishes what was measured, what unit was analysed, and what inference was claimed – a core skill for methods sections.
• Handles bilingual requests: Works with English manuscripts and Chinese academic drafts (统计审查, 样本量, 多重比较) for publication-ready wording.
• Generates reviewer-ready responses: Drafts replies to reviewer comments about statistics, aligning with Nature's reporting expectations.
• Enforces rigor without overreach: Defaults to transparency auditing unless raw data and explicit computation requests are provided – safe for agents.

Practical scenarios

Pre-submission statistical self-audit

A user pastes the Methods and Results sections. The agent runs the skill, identifies missing randomization/blinding details, and suggests concrete edits to match Nature's reporting checklist.

Reviewer comment triage

A revision letter includes: "Please clarify whether replicates are biological or technical and justify the multiple-comparison correction." The agent drafts a precise, bounded response that addresses each point.

Chinese manuscript translation for international submission

A researcher submits a Chinese draft with a 统计方法 section. The agent rewrites it into clear, journal-ready English statistical reporting, preserving technical accuracy.

Add it to your agent workflow

Install the skill directly into your agent's toolchain:

npx skills add Boom5426/Nature-Paper-Skills --skill stats-reporting-audit

Then invoke it with a simple prompt: "Audit the statistical reporting in this Results section for a Nature submission." The skill returns a structured report with missing items and suggested fixes. For a deeper dive, see the skill page on OpenAgentSkill for usage examples and community notes.

Compare before adopting

• Quality signals: Check the skill's recent commits, issue responses, and whether the README reflects current Nature guidelines (e.g., 2023+ updates on effect sizes and confidence intervals).
• Maintenance freshness: Look at last update date; a dormant skill may miss evolving journal policies.
• Alternatives: Compare with generic statistical checklist prompts or other security/audit skills. Does this one handle bilingual and reviewer-specific cases better?
• Workflow fit: Does your agent already have a statistical analysis tool? This skill is for reporting, not computation – ensure it complements rather than duplicates.

Why it is worth tracking

With 481 stars and an Apache-2.0 license, this skill shows clear community uptake. It fills a niche that generic summarization tools miss: precise, reproducible statistical reporting for high-stakes submissions. Track it if you build agents for academic researchers, journal editors, or peer-review support. Evaluate it when you need to upgrade your agent's ability to audit methods sections – it's a practical, low-risk addition that directly improves output quality.