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Audit score 90

nature-data

yuan1z0825/nature-skills

Prepare Nature-ready data availability statements, repository plans, and FAIR metadata for academic manuscripts.

What is nature-data?

This skill helps authors draft, audit, and revise data availability statements, dataset citations, and FAIR metadata checklists for Nature-family journals and other academic publications. Use it when preparing data sharing sections, selecting repositories, handling restricted data, or writing data statements in English or Chinese.

  • Draft and audit data availability statements for journal submissions
  • Classify datasets into access routes (public repository, controlled access, restricted, etc.)
  • Select appropriate data repositories and generate accession/DOI strategies
  • Create formal dataset citations in DataCite style
  • Run FAIR metadata compliance audits
  • Support Chinese-to-English translation for data statements

How to install nature-data

npx skills add https://github.com/yuan1z0825/nature-skills --skill nature-data
Claude Code
Cursor
Windsurf
Cline

How to use nature-data

  1. 1.Load the manifest and core layer files (stance, Chinese-mode guidance, and eight-step workflow)
  2. 2.Confirm the target journal and user language (English or Chinese)
  3. 3.Inventory all supporting datasets and classify each into an access route
  4. 4.Choose repository and identifier strategy before drafting
  5. 5.Draft the statement with explicit dataset-to-location mapping
  6. 6.Add formal dataset citations
  7. 7.Run the FAIR/metadata audit
  8. 8.Return ready-to-paste text and flag any unresolved fields

Use cases

Good for
  • Preparing a data availability statement for a Nature submission with multiple supporting datasets
  • Selecting an appropriate repository for sensitive or restricted research data
  • Converting a Chinese data availability statement to publication-ready English
  • Auditing existing dataset citations and metadata for FAIR compliance
  • Planning data sharing strategy for a manuscript with code, supplementary data, and third-party restrictions
Who it's for
  • Researchers preparing Nature-family journal submissions
  • Authors writing data availability sections for any academic journal
  • Chinese-speaking scientists preparing English manuscripts
  • Data stewards and research coordinators managing publication workflows

nature-data FAQ

What should I do if I don't have a DOI or accession number yet?

Flag the dataset as 'pending repository submission' in the statement. Do not invent DOIs or accession numbers. The skill will help you choose a repository and identifier strategy before finalizing the statement.

Can I use 'available upon request' for all restricted data?

No. 'Available upon request' is flagged as weak unless there is a specific legal, ethical, commercial, or third-party restriction. Follow the access-route classification to justify the restriction explicitly.

How does this skill handle Chinese authors?

If you write in Chinese, the skill accepts Chinese input, drafts English output, and converts terms precisely using the Chinese-mode guidance. A 中文核对 (Chinese verification) block is added to ensure accuracy.

What if my journal has different data requirements than Nature?

Journal-specific instructions take precedence. The skill will confirm your target journal and adjust the statement accordingly.

Does this skill generate FAIR metadata automatically?

No. The skill runs a FAIR/metadata audit checklist and flags missing elements (license, access conditions, metadata standards, etc.), but you provide the actual metadata values.

Full instructions (SKILL.md)

Source of truth, from yuan1z0825/nature-skills.


name: nature-data description: >- Prepare, audit, or revise Nature-ready Data Availability statements, data repository plans, dataset citations, and FAIR metadata checklists for manuscripts. Use when the user asks about Nature data availability, research data sharing, repository selection, accession numbers, restricted or sensitive data, source data, supplementary datasets, DataCite-style dataset references, FAIR metadata for academic publication, or Chinese-to-English data availability wording for Chinese-speaking authors preparing Nature-family submissions. Also trigger on general academic-writing data needs even without the word "Nature", such as writing a data availability statement for any journal, code/data sharing sections, repository selection while writing a paper, and Chinese phrasings like 数据可用性声明、数据可用性、 数据共享、代码可用性、学术写作数据声明、写数据声明、数据存放、数据仓库选择. version: 2.0.0 author: Yuan1z skill, refactored into static/dynamic layers

Nature Data Availability — Router

This skill is split into two layers:

  • A static layer under static/ that holds versioned, reusable content fragments (the default stance and source hierarchy, the Chinese-user operating mode, and the workflow with output format).
  • A dynamic layer (this file plus manifest.yaml) that loads the core every time and reaches for the deeper policy/repository/FAIR references only when a step needs them.

Do not try to apply the data-availability logic from memory or from this router. Always load fragments from disk as described below.

Routing protocol

Follow these four steps every time the skill is invoked.

1. Load the manifest and the core layer

Read manifest.yaml. Then read every file listed under always_load:

  • static/core/stance.md — what the data-availability package is, the default stance, and the source hierarchy.
  • static/core/chinese-mode.md — how to operate when the user writes in Chinese (accept Chinese, draft English, convert terms precisely).
  • static/core/workflow.md — the eight-step workflow and the output format.

2. No content axis — confirm journal and language inline

Unlike nature-writing or nature-figure, nature-data has no fragment axis. Its variation is handled at runtime, not by loading different content bodies:

  • journal/article type — if journal-specific instructions conflict with this skill, follow the journal.
  • access route — each dataset is classified into one route (public repository, controlled access, within paper, reused public, third-party restricted, justified request, or not applicable).
  • user language — if the user writes Chinese, follow core/chinese-mode.md and add the 中文核对 block.

3. Run the workflow

Follow the eight-step workflow in core/workflow.md: identify the journal, inventory every supporting dataset, classify each into one access route, choose repository and identifier strategy before drafting, draft the statement with explicit dataset-to-location mapping, add formal dataset citations, run the FAIR/metadata audit, and return ready-to-paste text plus unresolved fields.

Do not invent DOIs, accession numbers, repository names, licences, embargo dates, ethics approvals, access committees, or data-use conditions. Flag "available upon request" as weak unless there is a specific legal, ethical, commercial, or third-party restriction.

4. Reach for references only when needed

The files under references/ are deep references, not defaults. Open them on demand per the references.on_demand table in the manifest — for example references/policy-principles.md for the governing rules and edge cases, references/repository-and-identifiers.md for repository/accession/DOI choices, references/statement-patterns.md for ready-to-adapt statements, references/fair-metadata-checklist.md for the FAIR audit, references/chinese-author-alignment.md for Chinese wording, and references/source-basis.md to justify a rule with its official source.

Why this split

  • The static layer is versioned and reviewable; the core stays small for a normal statement.
  • The dynamic layer keeps each invocation cheap: the policy, repository, and FAIR depth load only when a step needs them.
  • The router itself is short on purpose. Update fragments and references, not this file, when adding scope.
  • This structure mirrors nature-writing, nature-polishing, nature-reader, nature-paper2ppt, nature-figure, nature-citation, and nature-response.