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⚙ Needs: Python (matplotlib/seaborn) or R (ggplot2/patchwork/…

Nature-grade scientific figures in Python or R

Create, revise, audit and export submission-ready manuscript figures — matplotlib/seaborn or ggplot2 — plus an explicit AI-schematic route

At a glance
What
Create, revise, audit and export submission-ready manuscript figures — matplotlib/seaborn or ggplot2 — plus an explicit AI-schematic route
Cost
Free
Needs
Python (matplotlib/seaborn) or R (ggplot2/patchwork/ComplexHeatmap) installed for the plotting route; your own image-generation API key (billed) only if you want the explicit AI-schematic route; scientific figure data of your own
Install
Copy the installer prompt below into your Muse — your agent does the rest.

Version:

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Created by: @yuan1z0825
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Install

Prerequisites: Python (matplotlib/seaborn) or R (ggplot2/patchwork/ComplexHeatmap) installed for the plotting route; your own image-generation API key (billed) only if you want the explicit AI-schematic route; scientific figure data of your own Install "Nature-grade scientific figures in Python or R" for me. It teaches an agent @yuan1z0825's nature-figure router: resolve one plotting backend (Python or R, saved as default), apply the figure contract and restrained-palette stance, build multi-panel figures with inferential panel roles, and run the rendered QA gate (panel-alignment and collision audits at final physical size, mandatory re-audit after any change) — plus flagship-Nature or NMI production contracts when targeting those journals, and a separate explicit route for AI-generated graphical abstracts/schematics with policy gate and human scientific review. Apache-2.0 licensed (declared in the source repo). Repository: https://github.com/yuan1z0825/nature-skills/blob/main/skills/nature-figure/SKILL.md 1. Fetch the SKILL.md file (and any helper files) from the repository path into a temporary folder and summarize what it does in one or two sentences. 2. Safety check: review the SKILL.md and scripts for anything suspicious (unexpected network calls, shell commands, credential harvesting). This repo should contain zero secrets in code, credentials only via the secure vault, allowed hosts declared in the SKILL.md. Verify that holds here; STOP on any red flag and tell me. 3. Install it as a skill: copy SKILL.md and its helper files into the agent's skills directory, in a folder named "nature-figure". 4. Verify with no network calls: frontmatter valid, files in place. 5. Report what was installed, where, and what I still need to do myself (e.g. answer "Python or R?" once when the agent asks, provide your figure data; the AI-schematic route needs your own image-generation API key). GitHub is optional: if I have a GitHub account or the gh CLI, you may use it; otherwise public access is fine. Never require it unless it's in the prerequisites above. Rules: don't touch anything outside the temp folder and the install target. If anything looks off, stop and ask me.

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Questions

How do I install a build?

Every product page includes a copy-paste install prompt. Paste it into your Muse and it sets the build up for you — no manual configuration.

Where does my money go?

Straight to the seller. Skill Harbor never processes payments: checkout happens on the seller’s own page, usually Stripe.

What does the ✓ next to a creator’s name mean?

It means we confirmed the identity of the person behind the listing. It says nothing about the code itself — always check a build before installing it.