Generate publication-ready academic figures with engine selection and validation.
npx skills add https://github.com/wentorai/Research-Claw --skill plotting-sop
Please help me install this Agent Skill. Skill: Plotting SOP Source: https://github.com/wentorai/Research-Claw/tree/main/skills/plotting-sop Command: npx skills add https://github.com/wentorai/Research-Claw --skill plotting-sop
This Skill removes the friction of producing research-quality figures by standardizing the end-to-end workflow from environment checks, to engine selection, to rendering and validation—so you can focus on the content, not formatting.
Ask: "Create a publication-ready line chart for my dataset and save it as a figure with an English caption."
High-intent search queries and answers about installing and using this skill.
Publication-ready academic figures are generated by selecting the appropriate rendering engine—Python charts, Mermaid diagrams, NanoBanana, or SVG—and executing deterministic generation with post-generation validation for DPI, English captions, and colorblind-safe palettes.
Rendering complex research diagrams is handled by the NanoBanana engine via OpenRouter, which provides a confirmation-first, cost-aware path to generate polished, publication-ready illustrations without manual formatting.
Yes, Mermaid diagrams and Python charts are supported together. An engine selection decision tree automatically evaluates your figure type and routes the request to the appropriate rendering engine, whether for structured diagrams or data visualizations.
Your data visualization fails publication standards if it lacks 300+ DPI, English labels, a white background, or a colorblind-safe palette. An academic style and quality checklist validates these requirements after every rendering attempt.
Yes, an OpenRouter API key is required to generate custom vector graphics with NanoBanana. The skill enforces a NanoBanana confirmation and API protocol, providing a cost-aware path before attempting complex diagram illustration.
Norman-buryInstall Miniconda and configure a reproducible Python data-visualization environment.
Ar9avRender publication-ready PNG figures and captions from plotting plans and experimental logs.
jmerkowGuide Mermaid and SVG diagram rendering across tools like mmdc and rsvg-convert.
lix965996-artGenerate LaTeX-compatible vector PDF figures and statistics tables from JSON experiment data.
