Nature Figure
Create, revise, audit, and export manuscript scientific figures in Python or R.
Install
npx skills add Yuan1z0825/nature-skills --skill nature-figure -g -a claude-code -y- Repository
- Yuan1z0825/nature-skills51.7k
- Category
- Data and ML
- Updated
- 4d ago
- License
- Apache-2.0
- Context cost
- Mediumabout 2,992 tokens
- Runs scripts
- Yes, review before use
What it does
Create, revise, audit, and export manuscript scientific figures in Python or R. Use for 论文配图、科研绘图、多面板图 and submission-ready plots, or explicitly requested AI-generated graphical abstracts and mechanism schematics. Not for interactive dashboards, data cleaning, or statistics-only analysis.
Nature Figure Making, 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.
0. Check for graphical-abstract and AI-schematic routes
For every graphical-abstract planning, generation, revision, or audit task that uses AI, read references/ai-graphical-abstract-workflow.md first. It owns the message/audience brief, composition and palette workflow, policy gate, human scientific review, disclosure boundary, and provenance requirements. A Nature Careers article is practitioner advice, not submission clearance; verify the current official policy for the exact target journal.
If the request is planning or auditing only, do not ask for Python or R unless the user also asks to render or revise a data-driven figure.
If the user explicitly asks to generate a manuscript schematic, graphical abstract, mechanism diagram, concept illustration, or paper schematic with OpenRouter, GPT Image 2, an image-generation API, or similar wording, do not ask "Python or R?". This is a non-plotting AI-schematic route.
For this route:
- Read manifest.yaml and the
always_loadfiles. - Read references/ai-graphical-abstract-workflow.md.
- Read references/openrouter-image-generation.md.
- Use scripts/generate_openrouter_schematic.py when the user wants a real API call or a reproducible payload.
- Treat output as a draft schematic / graphical abstract, not as a quantitative data panel. Do not invent experimental values, author logos, institutional marks, or unsupported mechanisms. Keep internal usefulness separate from submission eligibility.
