
Nature Data Availability
FreeStreamline your data availability statements for academic publishing.
Free · Opens the source repo
What Nature Data Availability does
The Nature Data Availability skill is designed to assist researchers and authors in preparing, auditing, and revising data availability statements, data repository plans, and FAIR metadata checklists specifically for submissions to Nature journals. This skill is particularly useful for academics who need to ensure compliance with the data sharing requirements set forth by Nature and similar publications. It provides a structured approach to drafting data availability statements, ensuring that all necessary components are included and correctly formatted.
The skill operates through a two-layer system: a static layer containing reusable content fragments and a dynamic layer that executes a detailed workflow every time it is invoked. Users begin by loading the manifest and core content, which includes essential guidelines on stance and workflow. The skill then dynamically confirms the journal type and user language, allowing for tailored responses that meet specific requirements. This is especially beneficial for Chinese-speaking authors who may need assistance in translating data availability terminology into English.
The eight-step workflow guides users through identifying the relevant journal, classifying datasets, selecting appropriate repositories, and drafting the data availability statement. This structured process helps eliminate common pitfalls in data sharing documentation, such as vague statements or incorrect citations. The skill also emphasizes the importance of adhering to the FAIR principles, ensuring that the datasets are Findable, Accessible, Interoperable, and Reusable.
Overall, this skill is ideal for researchers, data managers, and authors aiming to enhance the clarity and compliance of their data availability statements, particularly when submitting to high-impact journals like Nature. It streamlines the often complex process of data sharing in academic writing, making it easier for users to meet the stringent requirements of scholarly publications.
When to use it
Use this skill when drafting data availability statements for submissions to Nature journals or when needing guidance on data sharing practices in academic writing.
When not to use it
This skill may not be suitable for non-academic contexts or when dealing with journals that have significantly different data sharing requirements.
What you can build with it
Preparing for Nature Submission
Use this skill to draft compliant data availability statements for your manuscript submission to Nature, ensuring all requirements are met.
Translating Data Statements
If you're a Chinese-speaking author, utilize the Chinese mode to accurately translate and draft your data availability statements in English.
Auditing Existing Statements
Leverage the skill to review and revise your current data availability statements, ensuring they align with FAIR principles and journal standards.
How to install Nature Data Availability
View source1. Install with the skills CLI
npx skills add yuan1z0825/nature-skills/nature-data --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by yuan1z0825Nature 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.mdand 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.
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.
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, andnature-response.
Frequently asked questions about Nature Data Availability
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