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nature-data

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.

Install / Use

npx skills add Yuan1z0825/nature-skills --skill nature-data

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

86/100

Supported Platforms

Universal

Tags

Our assessment of nature-data

nature-data scores 86/100 on our quality scale, 2324th of 4,648 Development & Engineering skills we index (top 50%).

Its SKILL.md is 3.7 KB long, split into 6 sections and no code examples: a solid amount of guidance for an agent.

With 44,346 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
26/30
Structure
11/20
Description
15/15
Adoption
20/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated about 2 months ago, so nature-data is actively maintained.
  • Our last check on 2026-11-03 found the source still online.
  • It is released under the Apache-2.0 license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

Safety scan

No issues found

Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful.

AI review by kimi-k2.7-code on 2026-09-25. Automated pattern scan on 2026-09-25. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.

nature-data compared with similar skills

All 4 of these similar skills score higher than nature-data; compare them before choosing.

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taste-skillby Leonxlnx100112.0k1d agoCLAUDE.md
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Frequently asked questions

How do I install nature-data?
Run npx skills add Yuan1z0825/nature-skills --skill nature-data. The install tabs above show the steps for each supported agent.
Which AI agents does nature-data work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is nature-data safe to use?
Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful. It is Apache-2.0-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is nature-data still maintained?
The repository was last updated about 2 months ago, so nature-data is actively maintained.

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.

Related Skills

View on GitHub
GitHub Stars44.3k
CategoryDevelopment
Updated1mo ago
Forks2.3k

Languages

Python

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions
nature-data — Universal Skill: Install & Safety Check | SkillAgent