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Agent skill

Nature Figure

by NeuroAIHub in NeuroAIHub/BrainPilot

Submission-grade Nature/high-impact journal figure workflow for Python or R.

AGPL-3.0Auto-check passedData & Analytics

Install Nature Figure

skills CLI
$ npx skills add NeuroAIHub/BrainPilot --skill nature-figure -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install NeuroAIHub/BrainPilot nature-figure --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/NeuroAIHub/BrainPilot.git skills-src && mkdir -p .claude/skills && cp -r skills-src/packages/skills/skills/13_Visualization/nature-figure .claude/skills/nature-figure && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
nature-figure
GitHub stars
1.1k
Used in
1 other repo
Token cost
~1.3k tokens
SKILL.md length
536 words
Files
123 (incl. references, assets)
Skills in repo
59
Repo updated
First seen
Licence
AGPL-3.0

At a glance

Submission-grade Nature/high-impact journal figure workflow for Python or R.

  • Works in 5 steps: Load the manifest and the core layer → Resolve the backend — a blocking gate → Load the matching backend fragment → …
  • The user asks to create
  • SKILL.md covers Routing protocol and Why this split
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Nature Figure is an agent skill from NeuroAIHub/BrainPilot. Submission-grade Nature/high-impact journal figure workflow for Python or R. Use whenever the user asks to create, revise, audit, or polish manuscript figures, multi-panel scientific plots, figures4papers-style matplotlib plots, or journal-ready SVG/PDF/TIFF outputs, especially for Nature-family or other high-impact journals. Before plotting, define the figure's conclusion, evidence logic, export needs, and review risks. If the user has not chosen Python or R, ask "Python or R?" and stop. Use only the selected…

Its SKILL.md is about 1.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 126 other files, including reference files and assets (for example `README.md`).

It sits in Data & Analytics, covering Data visualization. It works with Python, Matplotlib, Seaborn and Adobe Illustrator. The repository describes itself as: BrainPilot: Automating Brain Discovery with Agentic Research. The licence is AGPL-3.0.

When your agent uses it

  • The user asks to create
  • Polish manuscript figures
  • Multi-panel scientific plots
  • Figures4papers-style matplotlib plots

Example prompts

  • “Python or R?”
  • “Nature”
  • “/nature-figure”

Requirements

  • Python 3

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Load the manifest and the core layer
  2. Resolve the backend — a blocking gate
  3. Load the matching backend fragment
  4. Build the figure using the loaded material
  5. Reach for references only when needed

What it can do on your machine

Read from SKILL.md and the folder at commit 93f6855. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Nature Figure loads about 1.3k tokens when it runs, and up to ~23k if it reads all its reference files. Until then it costs about 245 tokens; SKILL.md has 536 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~245
When it runs · the whole SKILL.md, loaded when a task matches
~1.3k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~23k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from NeuroAIHub/BrainPilot at commit 93f6855, republished under its AGPL-3.0 licence (© NeuroAIHub). 536 words, ~1,287 tokens.

Download SKILL.mdSave it as .claude/skills/nature-figure/SKILL.md (or your agent's skills folder). This skill also uses 122 other files; get the full folder from GitHub.
name
nature-figure
description
Submission-grade Nature/high-impact journal figure workflow for Python or R. Use whenever the user asks to create, revise, audit, or polish manuscript figures, multi-panel scientific plots, figures4papers-style matplotlib plots, or journal-ready SVG/PDF/TIFF outputs, especially for Nature-family or other high-impact journals. Before plotting, define the figure's conclusion, evidence logic, export needs, and review risks. If the user has not chosen Python or R, ask "Python or R?" and stop. Use only the selected backend for figure generation, previewing, exporting, and QA. Supports matplotlib/seaborn and ggplot2/patchwork/ComplexHeatmap. Not for dashboards or Illustrator/Figma-first infographics. Also trigger on general academic-writing figure needs even without the word "Nature", such as making figures/plots for a paper, scientific/academic plotting, data visualization for a manuscript, and Chinese phrasings like 论文配图、学术写作配图、科研绘图、科研作图、画图、作图、出图、论文图表、可视化.
version
2.0.0
author
Community contribution, refactored into static/dynamic layers

Nature Figure Making — Router

This skill is split into two layers:

  • A static layer under static/ that holds versioned, reusable content fragments (the figure contract and default stance, plus a per-backend quick-start for Python and R).
  • A dynamic layer (this file plus manifest.yaml) that detects the plotting backend and loads only the fragment needed for the current job. The large design, API, pattern, and QA material lives in on-demand references.

Do not try to apply the figure logic from memory or from this router. Always load fragments from disk as described below.

Routing protocol

Follow these five steps every time the skill is invoked.

1. Load the manifest and the core layer

Read manifest.yaml. It declares the backend axis, the allowed values, and the file paths each value maps to.

Also read every file listed under always_load (static/core/contract.md and static/core/stance.md). These hold the figure contract, the backend gate, the missing-runtime rule, the privacy rule, and the default operating stance that apply to every figure job.

2. Resolve the backend — a blocking gate

Backend selection blocks everything else. Decide the backend value only from an explicit user choice or a clearly language-specific input file/workflow:

  • python — matplotlib / seaborn.
  • r — ggplot2 / patchwork / ComplexHeatmap.

If the user has not explicitly chosen, ask exactly one concise question — Python or R? — and stop. Do not default, guess, generate mock data, or write scripts before the answer. Only recommend a backend when the user explicitly asks you to choose; then use references/backend-selection.md, state the reason, and proceed. Once selected, the backend is exclusive for all drawing, previewing, exporting, and visual QA (see core/contract.md).

3. Load the matching backend fragment

After the backend is resolved, Read the mapped fragment (static/fragments/backend/python.md or static/fragments/backend/r.md). It carries the backend-only execution rule and the publication quick-start (rcParams/theme and export helper). Do not load the other backend's fragment.

Show full SKILL.md (231 more words)Show less
4. Build the figure using the loaded material

Apply the loaded material in this order:

  1. Figure contract (core/contract.md) — write the core conclusion, map the evidence chain, classify the archetype, set the journal/export contract, before any code.
  2. Default stance (core/stance.md) — archetype-first composition, hero panel, restrained palette, statistics/integrity as part of the figure.
  3. Backend fragment — the exclusive Python or R quick-start and execution rule.

The chart serves the scientific logic; aesthetic polish is subordinate to making the core conclusion clear, defensible, and reviewable.

5. 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/figure-contract.md to build the contract, references/api.md for the Python palette and helpers, references/r-workflow.md for R, references/design-theory.md for color/typography/export rationale, references/common-patterns.md and references/chart-types.md for layout/chart recipes, references/nature-2026-observations.md for real Nature page archetypes, references/qa-contract.md before final delivery, and references/tutorials.md / references/demos.md for worked examples.

Why this split

  • The static layer is versioned and reviewable. The backend gate is now explicit in the manifest rather than buried in prose.
  • The dynamic layer keeps each invocation cheap: only the selected backend's quick-start enters context, and the 2,600+ lines of reference 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, and nature-paper2ppt.

© NeuroAIHub, AGPL-3.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 122 other files (references, assets) in packages/skills/skills/13_Visualization/nature-figure of NeuroAIHub/BrainPilot.

  • SKILL.md
  • .gitignore
  • README.md
  • assets/chart-atlas/atlas-01-bar-charts.png
  • assets/chart-atlas/atlas-02-line-trends.png
  • assets/chart-atlas/atlas-03-heatmaps.png
  • assets/chart-atlas/atlas-04-scatter-bubble.png
  • assets/chart-atlas/atlas-05-radar-polar.png
  • assets/chart-atlas/atlas-06-distributions.png
  • assets/chart-atlas/atlas-07-forest-interval.png
  • assets/chart-atlas/atlas-08-area-stacked.png
  • assets/chart-atlas/atlas-09-image-plates.png
  • assets/chart-atlas/atlas-10-network-matrix.png
  • assets/figures4papers/assets/Dispersion_motivation.png
  • assets/figures4papers/assets/Dispersion_observation.png
  • assets/figures4papers/assets/Dispersion_observation_distillation.png
  • assets/figures4papers/assets/ImmunoStruct_contrastive.png
  • … and 106 more

Open the folder on GitHubat commit 93f6855

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in NeuroAIHub/BrainPilot, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Nature Figure next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Nature Figure compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Nature Figure this skillNeuroAIHub/BrainPilot1.1k1 repos~1.3kAutomated safety check: PassAGPL-3.0
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Nature FigureCitrus-bit/Anaxa1202 repos~2.7kAutomated safety check: PassMIT
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Release Evidence WorkflowAli-Marandi/ClimateDataAnalyzer107—~1.6kAutomated safety check: PassMIT

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Works with

Categories

Questions about Nature Figure

What does Nature Figure do?

Submission-grade Nature/high-impact journal figure workflow for Python or R. Nature Figure is an agent skill from NeuroAIHub/BrainPilot. Submission-grade Nature/high-impact journal figure workflow for Python or R.

When should I use Nature Figure?

Nature Figure fits situations like: the user asks to create; polish manuscript figures; multi-panel scientific plots; figures4papers-style matplotlib plots.

How do I install Nature Figure in Claude Code?

Run `npx skills add NeuroAIHub/BrainPilot --skill nature-figure -a claude-code`. Or copy the skill folder (packages/skills/skills/13_Visualization/nature-figure in NeuroAIHub/BrainPilot) into .claude/skills/nature-figure in your project. Claude Code loads it when a task matches its description.

How do I install Nature Figure in Codex?

Run `npx skills add NeuroAIHub/BrainPilot --skill nature-figure -a codex`. Or copy the skill folder (packages/skills/skills/13_Visualization/nature-figure in NeuroAIHub/BrainPilot) into .agents/skills/nature-figure in your project. Codex loads it when a task matches its description.

Can I use Nature Figure in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add NeuroAIHub/BrainPilot --skill nature-figure -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/nature-figure, .gemini/skills/nature-figure, .github/skills/nature-figure and .opencode/skills/nature-figure in your project.

What does Nature Figure need to run?

SKILL.md names no scripts, command-line tools or credentials: Nature Figure is instructions for the agent only. Our summary lists: Python 3.

Does Nature Figure access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Nature Figure safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Nature Figure use?

Nature Figure is published under the AGPL-3.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Nature Figure use?

About 1.3k tokens (SKILL.md is roughly 5.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 22k tokens, read only when the agent opens those files.

What are the alternatives to Nature Figure?

Skills that share tags, products or a category with Nature Figure: Ieee Figure Table (CloudWave818/ieee-skills, 359 stars), Nature Figure (Citrus-bit/Anaxa, 120 stars), Nature Figure (Tai609/NebulaMat, 100 stars) and CJK Font Setup for Plots (xjtulyc/MedgeClaw, 617 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Nature Figure?

NeuroAIHub (a GitHub organization) maintains it in NeuroAIHub/BrainPilot, which has 1,062 GitHub stars. The repository holds 59 skills in this directory. The repository was last updated on October 2, 2026.

Source: NeuroAIHub/BrainPilot on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.