paper-illustration-image2

Generate publication-quality academic figures with layout, palette, typography, and arrow semantics.

1|1|Updated May 19, 2026
One-click install
npx skills add https://github.com/zhuyingqin/ARIS-WEB --skill paper-illustration-image2-zhuyingqin
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: paper-illustration-image2
Source: https://github.com/zhuyingqin/ARIS-WEB/tree/main/crates/runtime/assets/skills/paper-illustration-image2
Command: npx skills add https://github.com/zhuyingqin/ARIS-WEB --skill paper-illustration-image2-zhuyingqin

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires codex, and includes scripts (resource) components.

What problem does it solve?

This Skill solves the problem of producing publication-quality academic figures without manually iterating on layout, styling, and arrow/label correctness.

Core Features & Use Cases

  • Multi-stage figure planning and review: Uses a planner/reviewer workflow to produce a precise, paper-appropriate figure prompt and then strictly score the result (target score 9/10).
  • Native image generation via local Codex bridge: Renders only through a local Codex app-server MCP bridge (codex-image2), avoiding non-native fallbacks.
  • Final artifact packaging for papers: Promotes the best accepted image to figure_final.png and emits latex_include.tex plus review_log.json and verify.json.

Quick Start

Generate a publication-quality architecture or method illustration for my paper by running the paper-illustration-image2 workflow in the current project workspace.

Frequently Asked Questions about paper-illustration-image2

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

FAQPage Schema
How do I generate publication-quality academic figures for my paper?▼

To generate publication-quality academic figures, this Skill uses an iterative multi-step planning and layout optimization workflow to produce paper-ready architecture diagrams and method illustrations with correct palette, typography, and arrow semantics. It strictly scores the visual output to target a 9/10 rating before finalizing the image.

Do I need a local Codex app-server to render native academic illustrations?▼

Yes, you need a local Codex app-server MCP bridge (codex-image2) to render native academic illustrations. The workflow requires this local native raster rendering bridge for explicit preflight, bounded render, and strict visual scoring, actively avoiding non-native fallbacks to ensure publication quality.

Can I integrate generated paper illustrations directly into LaTeX?▼

Yes, you can integrate generated paper illustrations directly into LaTeX. The workflow automatically packages the final accepted image as figure_final.png and emits a latex_include.tex file, allowing direct inclusion of the academic figure into your LaTeX document pipeline.

What is the best way to ensure correct layout and label semantics in architecture diagrams?▼

The best way to ensure correct layout and label semantics in architecture diagrams is using a planner and reviewer workflow that iteratively optimizes the figure layout. This process applies strict style verification to validate arrow and label semantics before promoting the image to a finalized paper-ready artifact.

What artifacts are produced when finalizing method illustration pipelines?▼

Finalizing method illustration pipelines produces three main artifacts: figure_final.png containing the best accepted image, latex_include.tex for document integration, and review_log.json alongside verify.json to document the strict visual scoring and style verification results.

What are the limitations of using native image rendering for academic figures?▼

A key limitation of native image rendering for academic figures is the strict dependency on the local Codex app-server MCP bridge. The workflow avoids non-native fallbacks, meaning the bounded render and preflight checks will fail if the local codex-image2 environment is not properly configured.