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paper-illustration-image2

Generate paper-ready academic figures with CVPR/ICLR/NeurIPS style constraints.

2|1|Updated Apr 19, 2026
Search Tags:#diagram generation#iterative refinement#academic figures#CVPR style#mcp image rendering#workflow illustration#native image generation
One-click install
npx skills add https://github.com/raja21068/AutoResearch --skill paper-illustration-image2-raja21068
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: paper-illustration-image2
Source: https://github.com/raja21068/AutoResearch/tree/main/skills/aris/paper-illustration-image2
Command: npx skills add https://github.com/raja21068/AutoResearch --skill paper-illustration-image2-raja21068

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps you generate publication-quality academic illustration images with correct layout, styling, and readable labels, avoiding the trial-and-error that usually makes diagram-generation unusable for papers.

Core Features & Use Cases

  • Execution-grounded, multi-stage generation: plans the figure, optimizes layout, verifies CVPR/ICLR/NeurIPS-style constraints, generates a native raster via an MCP bridge, and then strictly reviews it.
  • Strict acceptance criteria with iterative refinement: scores outputs (target score ≥ 9), rejects unclear or non-paper-ready figures, and loops with specific improvement instructions up to a capped number of iterations.
  • Canonical integration artifacts: runs a required preflight step, finalizes to standardized outputs (including LaTeX include snippet and verification receipts), and verifies before reporting success.
  • Use Case: turn a paper method description like an end-to-end pipeline into a clean architecture/workflow figure with correct arrow direction, hierarchy, and print-friendly typography.

Quick Start

Ask for a paper-ready workflow diagram and run the Skill’s required preflight, then generate the figure through the Codex image2 bridge and finalize with verification.

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 CVPR or NeurIPS papers?▼

To generate publication-quality academic figures, provide a figure request to trigger structured prompt planning, enforce CVPR/ICLR/NeurIPS style constraints, and render native raster images through an MCP bridge with iterative visual scoring.

What's the best way to turn a paper method description into a clean workflow diagram?▼

Turning a paper method description into a workflow diagram involves planning the figure layout, optimizing hierarchy and arrow direction, verifying print-friendly typography, and rendering the output through an iterative refinement loop.

How does iterative refinement work when generating academic diagrams?▼

Iterative refinement for academic diagrams works by scoring generated outputs against a target score of 9 or higher, rejecting unclear figures, and looping with specific improvement instructions up to a capped number of iterations until visual constraints pass.

Can I use Codex image generation to create LaTeX-ready illustrations?▼

Yes, you can use the Codex image2 MCP bridge to create LaTeX-ready illustrations by running a required preflight step, generating the native raster image, and finalizing to standardized outputs including a LaTeX include snippet and verification receipts.

Why does my generated paper diagram fail the visual acceptance check?▼

A generated paper diagram fails the visual acceptance check when it scores below the target score of 9, contains unclear labels, violates CVPR style constraints, or lacks print-friendly typography, triggering specific improvement instructions for another iteration.

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