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nature-data

yuan1z0825/nature-skills

Draft and audit Data Availability statements, dataset access routes, and FAIR metadata for research manuscripts.

What is nature-data?

This skill helps researchers and authors create or review Data/Code Availability statements for manuscript submissions. It guides dataset classification, repository selection, FAIR metadata compliance, and citation formatting—essential for journals like Nature and Nature Machine Intelligence that mandate transparent data-sharing policies.

  • Route datasets into access categories (public repository, controlled access, within paper, reused public, third-party restricted, justified request, or not applicable)
  • Draft journal-compliant Data Availability and Code Availability statements with explicit dataset-to-location mapping
  • Audit existing statements for gaps, missing identifiers, and FAIR metadata compliance
  • Classify datasets and select appropriate repositories with DOI/accession strategies
  • Generate formal dataset citations and access-condition documentation
  • Support journal-specific requirements (Nature, Nature Machine Intelligence, and others)

How to install nature-data

npx skills add https://github.com/yuan1z0825/nature-skills --skill nature-data
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How to use nature-data

  1. 1.Confirm the target journal and any journal-specific data-sharing requirements
  2. 2.Inventory all supporting datasets used in the study
  3. 3.Classify each dataset into one access route (public, controlled, embedded, reused, restricted, or request-based)
  4. 4.Select appropriate repositories and identifier strategies (DOI, accession number, etc.)
  5. 5.Draft the Data Availability statement with explicit mapping of datasets to locations and access conditions
  6. 6.Add formal dataset citations and document any embargoes or restrictions
  7. 7.Run the FAIR metadata audit against the checklist
  8. 8.Return ready-to-paste statement text and flag any unresolved fields for manual completion

Use cases

Good for
  • Preparing a manuscript submission to Nature or Nature Machine Intelligence with complete data-sharing documentation
  • Auditing an existing Data Availability statement for missing repository links or access conditions
  • Planning dataset deposition strategy across multiple repositories before manuscript drafting
  • Ensuring FAIR (Findable, Accessible, Interoperable, Reusable) metadata compliance for research datasets
  • Drafting statements for controlled-access or restricted datasets with legal or ethical constraints
Who it's for
  • Research authors preparing manuscripts for high-impact journals
  • Corresponding authors managing data-sharing compliance
  • Research data managers planning repository strategies
  • Journal editors and reviewers checking data-availability statements

nature-data FAQ

Should I use this skill for general data cleaning or statistical analysis?

No. This skill is specifically for Data Availability statements, dataset access routes, and FAIR metadata. Use other skills for data cleaning, transformation, or statistical analysis.

What if my dataset has legal or ethical restrictions on sharing?

Classify it into the appropriate restricted route (controlled access, justified request, or third-party restricted), document the specific restriction, and flag it in the statement. Do not invent access conditions; use only those that actually apply.

Can this skill handle journal-specific requirements?

Yes. The skill checks journal-specific instructions (e.g., Nature's mandatory-deposition rules, Nature Machine Intelligence's separate Code Availability section) and prioritizes them over general guidance.

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

The skill will flag unresolved identifiers and guide you to obtain them before submission. It does not invent DOIs or accession numbers.

Does this skill support non-English manuscripts?

Yes. If you write in Chinese or request Chinese guidance, the skill loads Chinese-mode resources and provides a 中文核对 (Chinese verification) block alongside English text.

Full instructions (SKILL.md)

Source of truth, from yuan1z0825/nature-skills.


name: nature-data description: "Draft or audit manuscript Data/Code Availability statements, dataset access routes, repository plans, and FAIR metadata. Use for 数据可用性声明、数据共享、数据仓库选择 and dataset citations; not general data cleaning or statistical analysis." metadata: author: Yuan1z skill, refactored into static/dynamic layers

Nature Data Availability — Router

Routing protocol

For a new task, load the core and matching resources below. Reuse already loaded guidance on follow-ups; load more only when the task needs it.

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/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 or requests Chinese guidance, read static/core/chinese-mode.md and add the 中文核对 block unless the user requested statement text only.

3. Run the workflow

For a wording edit or audit of one existing statement, preserve supplied repository identifiers and access conditions and check the affected claims. Report gaps relevant to that statement; do not require a full study-wide dataset inventory or repository redesign. Use the complete workflow below for a new data-sharing plan, full statement, or submission audit.

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.

When the target is the flagship journal Nature, also open references/nature-article-requirements.md for statement placement, mandatory-deposition routing, central-code review access, materials and structure-file checks.

When the target is Nature Machine Intelligence, open ../nature-shared/journal-formats/nature-machine-intelligence.md. Enforce a Data Availability statement and a separate Code availability section after it and before references; check reviewer access, precise restrictions, repository/identifier quality and the Software Submission Checklist for newly developed central code.