skills.rest
leonardodalinky
leonardodalinkyCOMMUNITY
Explore all skills by this author →
GitHub

plotting-agent

Generate publication-ready PNG figures from outline.json specifications using matplotlib.

87|7|Updated Oct 3, 2025
Search Tags:#research#matplotlib#generate#figures#plots#paperbanana
One-click install
npx skills add https://github.com/leonardodalinky/SciDER --skill plotting-agent
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: plotting-agent
Source: https://github.com/leonardodalinky/SciDER/tree/main/.scider/skills/plotting-agent
Command: npx skills add https://github.com/leonardodalinky/SciDER --skill plotting-agent

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires matplotlib, numpy, pillow, and includes scripts (resource) and references (resource) components.

What problem does it solve?

Researchers need to produce publication‑ready plots and diagrams from experiment logs and idea documents, a process that is time‑consuming and error‑prone.

Core Features & Use Cases

  • Automated rendering: Generates PNG figures at 300 DPI following strict aspect‑ratio tables.
  • Multi‑modal critique: Optionally refines images using a vision model loop.
  • Flexible back‑ends: Uses matplotlib by default or the PaperBanana backbone when available.
  • Caption generation: Produces context‑aware captions without manual editing. Apply it when writing a research paper that requires multiple plots, charts, or conceptual diagrams derived from structured outlines.

Quick Start

Invoke the plotting agent to generate all figures defined in the workspace’s outline.json.

Frequently Asked Questions about plotting-agent

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate publication-ready figures for a research paper from an outline?▼

You can generate publication-ready figures by applying this Skill to outline.json specifications and markdown inputs. It automatically renders plots and conceptual diagrams at 300 DPI with strict aspect ratios.

Can I use matplotlib to automatically create 300 DPI research plots from structured data?▼

Yes, matplotlib serves as the default backend to automatically render 300 DPI plots. The Skill processes your structured research outlines to produce charts without manual formatting.

Does this plotting tool support vision model critique for refining research diagrams?▼

Yes, the plotting tool supports an optional multi-modal critique loop. It uses a vision model to evaluate and iteratively refine generated research diagrams for better quality.

What is the best way to automate chart and caption generation for academic manuscripts?▼

Automating chart and caption generation is best handled by defining figure parameters in an outline.json file. The Skill then renders the plots and produces context-aware captions automatically.

Do I need a specific aspect ratio or DPI setting to create publication-quality plots?▼

No manual configuration is needed for DPI and aspect ratios. The Skill enforces 300 DPI output and follows strict aspect-ratio tables internally to meet publication standards.

When should I use the PaperBanana backend instead of matplotlib for research figures?▼

Use the PaperBanana backend instead of matplotlib when the optional PaperBanana backbone is available in your environment. It provides an alternative rendering engine for your research figures.

Related Skills

Explore More Education & Research Skills→
Agentic-AssetsAgentic-Assets

matplotlib

Create publication-quality figures with fine-grained control over plot elements.

Official
Advanced
Ar9avAr9av
635

plotting-agent

Render publication-ready PNG figures and captions from plotting plans and experimental logs.

Community
Advanced
jkitchinjkitchin
34

python-plotting

Select and apply Matplotlib, Seaborn, or Plotly for Python visualizations.

Community
Intermediate
galeepgaleep

matplotlib

Create and customize static, animated, and interactive plots with Matplotlib.

Community
Advanced