nature-data

Imported from yuan1z0825/nature-skills (skills/nature-data/SKILL.md) via skills.sh. Install upstream with npx skills add yuan1z0825/nature-skills --skill nature-data. Copyright stays with the author.

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.