
Nature Data Availability Helper
Drafts and audits journal Data/Code Availability statements, repository plans and FAIR metadata
- Repository
- Yuan1z0825/nature-skills
- Stars
- 51,827
- Licence
- Apache-2.0
- Files
- 15 files
What it does
Once installed, the agent helps researchers write or check the Data Availability and Code Availability statements that journals such as Nature require in manuscripts. It walks through an eight-step workflow: confirming the target journal, listing each supporting dataset, classifying how it can be accessed, choosing a repository and identifiers, drafting the statement, adding dataset citations, running a FAIR metadata check, and returning paste-ready text with open items flagged. It is explicitly told not to invent DOIs, accession numbers, licences or ethics approvals, and to treat vague 'available upon request' wording as weak.
Great for
- Researchers preparing a manuscript submission who need a compliant data availability statement
- Authors editing or auditing an existing statement for a specific journal
- Labs deciding which public repository to deposit data in and how to cite it
Skip it if
- General data cleaning or statistical analysis, which the skill explicitly excludes (the content is about publication policy, not analysis)
- Official journal compliance decisions: the output is a drafting aid and journal instructions take precedence, so editors should be consulted for final checks
- Datasets with legal or ethical restrictions that need real approvals; the agent cannot verify access committees or ethics approvals and could produce misleading wording if the user supplies no facts
Try asking
- “Draft a Data Availability statement for my Nature manuscript that uses three public datasets and one controlled-access cohort.”
- “Audit this existing 数据可用性声明 and tell me where the wording is vague or unsupported.”
- “Which repository should I use for my genomics dataset, and what identifiers do I need?”
- “Generate FAIR metadata checklist results and formal dataset citations for my paper's supporting data.”
Install in 3 steps
- 1
Download the skill
The ZIP contains the 15 original files, the Apache-2.0 licence and an attribution note.
nature-data.zip - 2
Add it to your agent
Claude Code (all projects)
mkdir -p ~/.claude/skills && unzip nature-data.zip -d ~/.claude/skills/Claude Code / Agent SDK (this project only)
mkdir -p .claude/skills && unzip nature-data.zip -d .claude/skills/Claude apps (web/desktop): Settings → Capabilities → Skills → Upload skill, and choose the ZIP.
- 3
Ask for the task
No special command needed — the agent reads the skill's description and loads it when your request matches. Try one of the prompts above.
Get better results
- Provide the target journal and article type up front, since journal rules override the skill's defaults.
- Supply real repository names, accession numbers and access conditions; the skill will flag rather than invent missing ones.
- For a single-statement wording edit, say so explicitly so the agent skips the full dataset inventory.
What's inside
- agents/openai.yaml
- manifest.yaml
- README_EN.md
- README.md
- references/chinese-author-alignment.md
- references/fair-metadata-checklist.md
- references/nature-article-requirements.md
- references/policy-principles.md
- references/repository-and-identifiers.md
- references/source-basis.md
- references/statement-patterns.md
- SKILL.md
- static/core/chinese-mode.md
- static/core/stance.md
- static/core/workflow.md
Redistributed unmodified from Yuan1z0825/nature-skills under the Apache-2.0 licence. The assessment was drafted with AI from the skill's files on 2026-10-29. Skills can instruct your agent to run code — read SKILL.md and any scripts before installing.