Nature Data
Draft Nature-ready Data Availability statements, repository plans, FAIR checklists, and dataset citations for manuscript submission.
Overview
Nature Data is an agent skill for the Build phase that prepares Nature-ready Data Availability statements, repository plans, FAIR checklists, and dataset citations for manuscripts.
Install
npx skills add https://github.com/yuan1z0825/nature-skills --skill nature-dataWhat is this skill?
- Nature Portfolio / Springer Nature data policy as the governing layer with FAIR and DataCite-style citations
- Produces Data Availability statement drafts, repository selection plan, accession placeholders, and restricted-data hand
- Flags vague phrasing (e.g. overly broad Chinese equivalents) and missing metadata before submission
- Chinese-to-English operating mode: accepts 中文 input, delivers English submission-ready text unless user requests otherwi
- Dual policy stack: Springer Nature / Nature Portfolio data policy plus FAIR and DataCite-style citation metadata
Adoption & trust: 2k installs on skills.sh; 17.8k GitHub stars; 3/3 security scanners passed (skills.sh audits).
What problem does it solve?
Your Nature submission needs a compliant data availability statement and repository plan but journal policy, FAIR metadata, and restricted-data wording are easy to get wrong.
Who is it for?
Authors targeting Nature Portfolio journals who need policy-aligned statements and dataset citation metadata without rereading Springer Nature guidance line by line.
Skip if: General open-source README data sections, non-academic SaaS privacy policies, or teams with no manuscript or dataset to describe.
When should I use this skill?
User asks about Nature data availability, research data sharing, repository selection, accession numbers, restricted data, supplementary datasets, FAIR metadata, or Chinese-to-English data availability wording for Nature
What do I get? / Deliverables
You receive English submission-ready availability text, a repository and citation plan, FAIR checklist coverage, and explicit flags for missing accession or access decisions.
- Data Availability statement (English, submission-ready)
- Repository plan with citation metadata and missing-information flags
Recommended Skills
Journey fit
Data availability packaging is documentation work tied to publication-ready artifacts—canonical on the docs shelf even when it informs validate-stage submission planning. The skill outputs statement text, repository plans, citations, and missing-information flags—exactly manuscript supporting documentation, not runtime code.
How it compares
Academic publication data-policy skill—not a generic cloud backup or database migration tool.
Common Questions / FAQ
Who is nature-data for?
Researchers and indie academic authors preparing Nature-family submissions, especially Chinese-speaking authors who need English statements with clear handling of restricted or sensitive data.
When should I use nature-data?
During Build docs when drafting or revising Data Availability sections, choosing repositories, adding accession numbers, or translating 数据可用性声明 intent into Nature-compliant English.
Is nature-data safe to install?
Manuscripts may contain unpublished or sensitive study details; review the Security Audits panel on this Prism page before sharing restricted dataset metadata with an agent.
SKILL.md
READMESKILL.md - Nature Data
# Nature Data Availability Skill Use this skill to turn a manuscript's supporting data into a transparent, Nature-ready data availability package: statement text, repository plan, dataset citations, and missing-information flags. The governing policy layer is Springer Nature / Nature Portfolio data policy. The implementation layer is FAIR data practice and DataCite-style citation metadata. ## Chinese-user operating mode When the user writes in Chinese, provides a Chinese manuscript note, or asks for "中文对应", "中英对照", "数据可用性声明", "数据获取声明", "原始数据", "数据存储库", or "受限数据": - Accept Chinese input naturally, but draft the final submission-ready statement in English unless the user explicitly asks for Chinese only. - Preserve a short Chinese explanation of unresolved decisions when it helps the author act. - Translate intent, not wording. Chinese phrases such as "可向通讯作者索取" are usually too vague for Nature-style English unless the restriction and access process are specified. - Convert Chinese repository/status descriptions into precise publication terms: `数据可用性声明` -> `Data Availability`; `原始数据` -> `raw data`; `处理后数据` -> `processed data`; `源数据` -> `source data`; `补充材料` -> `Supplementary Information`; `受限数据` -> `restricted data`; `合理请求` -> `reasonable request`, only with reason and review route. - Use `references/chinese-author-alignment.md` for Chinese terminology, common CN-to-EN failure modes, and bilingual intake questions. ## Default stance - Treat the Data Availability statement as a link between the paper's claims and the evidence needed to inspect, reproduce, or reuse them. - Do not invent DOIs, accession numbers, repository names, licences, embargo dates, ethics approvals, access committees, or data-use conditions. - Prefer public, discipline-specific repositories. Use generalist or institutional repositories only when no suitable community repository exists. - Describe both newly generated data and reused third-party data. - If data cannot be openly shared, state why, who controls access, how requests are evaluated, and what metadata or representative data can still be public. - Separate data, code, materials, and protocols unless the journal asks for a combined availability section. - Keep this skill focused on availability and metadata. Do not rewrite methods, analyze statistics, or polish the manuscript unless the user asks for those tasks separately. - Flag "available upon request" as weak unless there is a specific legal, ethical, commercial, or third-party restriction. ## Workflow 1. Identify the target journal and article type. If journal-specific instructions conflict with this skill, follow the journal. 2. Inventory every dataset needed to support the main and supplementary results: generated raw data, processed data, figure source data, secondary data, software outputs, models, tables, images, and files underlying statistical analysis. 3. Classify each dataset into one access route: `public repository`, `controlled access repository`, `within paper or supplement`, `reused public source`, `third-party restricted`, `available on justified request`, or `not applicable`. 4. Choose repository and identifier strategy before drafting text. Prefer DOI, accession number, Handle, ARK, or stable repository record over personal websites and temporary cloud links. 5. Draft the Data Availability stateme