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publication-figures

Generate publication-grade scientific figures with a validated shared palette, consistent typography, and render-time quality checks.

Skill by Garhorne0813

IndexedApache-2.0★ 1
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Install

Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/garhorne0813-publication-figures

Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.

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About

Generate publication-grade scientific figures with a validated shared palette, consistent typography, and render-time quality checks. Use whenever you create a chart, plot, or figure with matplotlib (or seaborn) in this workspace. The style applies the pi-science publication figure standard so every generated figure reads as one design system with the app's native charts.

Use cases: design, data, research

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Permissions

What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

Tools
No tools found
Secrets
None asked for
Install scripts
None found

Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/publication-figures

What's inside

Skill name
publication-figures
Description
Generate publication-grade scientific figures with a validated shared palette, consistent typography, and render-time quality checks. Use whenever you create a chart, plot, or figure with matplotlib (or seaborn) in this workspace. The style applies the pi-science publication figure standard so every generated figure reads as one design system with the app's native charts.
License
Apache-2.0
Instructions
68 lines in SKILL.md · view on GitHub

Files (2)

  • SKILL.md
  • pi_science.mplstyle

SKILL.md (first lines)

# Publication Figures

Make generated figures **publication-grade and on-system by default**. Every
figure you produce with matplotlib must use the bundled pi-science style, so a
figure in a report and a chart in the app's inspector read as one design system.

## Apply the style (always, before plotting)

The style file `pi_science.mplstyle` sits next to this SKILL.md. Load it at
the top of any figure script:

```python
import matplotlib.pyplot as plt
from pathlib import Path

# Resolve the style next to this skill's SKILL.md
STYLE = Path("skills/publication-figures/pi_science.mplstyle")
plt.style.use(str(STYLE)) if STYLE.exists() else plt.style.use("default")
```

If you cannot resolve the path, set the palette inline from the hex values below.

## The shared palette (single source of truth)

These hues match the pi-science app's native chart colors. Assign categorical
series in this **fixed order** — never a different order, never cycle the 9th hue.

| Slot | Name | Hex |
|------|------|-----|
| 1 | blue | `#2a78d6` |
| 2 | aqua | `#1baf7a` |
| 3 | yellow | `#eda100` |
| 4 | green | `#008300` |
| 5 | violet | `#4a3aa7` |
| 6 | red | `#e34948` |
| 7 | magenta | `#e87ba4` |
| 8 | orange | `#eb6834` |

**Sequential** (magnitude, one hue light → dark):
`#cde2fb` `#9ec5f4` `#6da7ec` `#3987e5` `#256abf` `#184f95` `#104281`

**Diverging**: blue ↔ neutral gray ↔ red, with a white/gray midpoint.

## Rules (from the pi-science visualization standard)

- **One y-axis.** Never two scales on one plot — use two charts side by side
  or index to a common base.
- **Categorical color = identity, assigned in slot order; sequential = one hue
  by magnitude; diverging = two hues + neutral midpoint.** Never a rainbow
  colormap.
- **Thin marks, recessive chrome:** 2px lines, ≥6pt markers, hairline y-grid
  only, no top/right spines (the style sets these).
- **Label selectively** — the endpoint or the extreme, never a number on every
  point. A legend is present for ≥2 series; a single series needs none (the
  title names it).
- **Text stays in ink** (dark), never the series color. Identity comes from
  the mark, not the text color.
- **Save clean:** `plt.savefig(path, dpi=200, bbox_inches="tight")`.

## Checklist before returning a figure

1. Style applied (palette + chrome from `pi_science.mplstyle`).
2. Series colors assigned in slot order; ≤8 series (else group into "Other").
3. Single y-axis; legend iff ≥2 series; axis labels + units present.
4. Figure is readable and non-empty when reopened at the saved resolution.
5. Saved to the workspace and referenced by path so it surfaces as an artifact.

From Garhorne0813/pi-science, Apache-2.0.

More from Garhorne0813/pi-science

Signals

Stars
1
Forks
1
Open issues
15
Last commit (this folder)
Jul 19, 2026 (3 months ago)

From GitHub (fetched Oct 24, 2026).

Details

License
Apache-2.0
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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publication-figures skill. Agent Mart. https://agentmart.dev/skills/garhorne0813-publication-figures (last updated 2026-10-24)