What does this skill do, and when should you use it?
This is a prompt-generation skill for academic paper figures, version 4.0.0, located at academic-figure-prompt-pastel/SKILL.md within the LigphiDonk/academic-figure-generator repository (which bundles two separate skills). It does not render images itself; instead it reads your paper and writes exhaustive English prompts for you to feed into any AI image generator. The aesthetic — pure white canvas, white panels with soft drop shadows, rounded Nunito/Poppins fonts, pastel token squares, colored keywords, and pill-shaped concept labels — was refined over 7 iterations to match top-tier ML conference figures from 2024–2025. The parent repo is a full FastAPI + React platform released under MIT; this skill is the standalone agent-skill slice of it.
- Step 1: reads the paper's source files to extract core concepts, methods, and data flow, identify figure placement, and understand math notation
- Step 2: presents four color schemes (P1 Warm ML, P2 Cool Research, P3 Earthy Warm, P4 custom) and waits for user confirmation
- Step 3: generates a full English prompt in three layers — global description, per-panel descriptions, style specifications — ending with a quality checklist
- The prompt covers token squares with exact hex fills and 1px borders, curve thumbnails, formulas, inline illustrations, decision trees, arrows, and pill labels
- Explanations are in Chinese, the prompt body is in English, and longer prompts are explicitly encouraged
- An ML/RL researcher submitting to ICLR/NeurIPS/ICML who needs prompt text for a method framework or architecture diagram
- A graduate student revising a paper who must add ablation-comparison or module-detail figures consistent with recent conference aesthetics
- A researcher with clear ideas but weak drawing skills who wants AI image tools to do the rendering
- A content author preparing multiple stylistically consistent diagrams for a technical report or survey
- A lab with specific palette needs (colorblind-friendly, journal style) that wants to define a custom token color scheme
- Users who need rendered images — this skill only produces English prompts; you must separately arrange and pay for an AI image tool, and final quality depends on how well that tool follows long prompts
- Journals demanding plain line art or other conventions — the skill is tightly bound to one aesthetic (modern pastel ML conference style)
- Teams expecting the README's platform-level claims of 50+ color schemes — SKILL.md defines only four schemes (P1–P4)
How do you install this skill?
- Shell / CLI
- Local filesystem
Any AI image generation tool (used externally by the user to render the prompts)
The repo supports one-line install via npx skills add LigphiDonk/academic-figure-generator (note: the README's manual-install examples copy the sibling skill folder academic-figure-prompt; for this skill the folder is academic-figure-prompt-pastel — copy that folder instead): into .claude/skills/ for Claude Code or .gemini/skills/ for Gemini CLI. It is a single SKILL.md with no extra dependencies or API keys (the image tool you later use is arranged separately).
tmp="$(mktemp -d)"
git clone --depth 1 https://github.com/LigphiDonk/academic-figure-generator.git "$tmp"
mkdir -p ~/.claude/skills
cp -R "$tmp/academic-figure-prompt-pastel" ~/.claude/skills/
rm -rf "$tmp"Generated from the source repository and skill path; it copies only this skill's folder. If the author's install steps above differ, follow those first. To scope it to one project, replace ~/.claude/skills with that project's .claude/skills.
How do you use this skill?
Once installed, send your agent any of these to trigger it:
- Generate an English prompt for a method framework figure for Section 3.2 of my paper, modern ML figure prompt, using the P1 Warm ML palette
- Create a prompt for an RL agent architecture diagram for my ICLR submission, pastel-style paper figure, reference image attached
- Use the Cool Research scheme to generate a prompt for an ablation-comparison figure with layout C (horizontal pipeline)
- Generate a modern ML-style prompt for a module-detail figure using a custom colorblind-friendly palette
After installation, trigger it in conversation with your AI coding assistant, e.g. "Read this paper and generate a prompt for a modern ML paper figure", or use the documented trigger phrases "pastel风格论文配图" / "modern ML figure prompt". The assistant analyzes the paper, shows color schemes P1–P4 for you to pick, then outputs a Markdown block with the complete English prompt (figure title, diagram type, recommended resolution). Paste the prompt into any AI image tool to render.
What are this skill's strengths and limitations?
- Style rules validated over 7 iterations and specified down to hex values, font sizes, shadow parameters, and pixel spacing — highly reproducible output
- English prompts (best for image tools) with Chinese interaction text — friendly to Chinese-speaking researchers
- Built-in color, element, and layout vocabularies covering framework, architecture, comparison, and module diagrams
- Layout is content-driven and asymmetric by design, avoiding cookie-cutter 2×2 grids
- Pure-text skill with zero runtime dependencies, MIT licensed, freely modifiable
- Generates prompts only, not images — you must separately arrange and pay for an AI image tool, and final quality depends on how well that tool follows long prompts
- Tightly bound to one aesthetic (modern pastel ML conference style); unsuitable for journals demanding plain line art or other conventions
- SKILL.md defines 4 color schemes (P1–P4), which conflicts with the README's platform-level claims of 50+ or 8 schemes — don't conflate them
- No test suite, sample output images, or adoption evidence in the source material; actual rendering quality can't be verified from documentation
How does this skill compare with similar options?
Side by side with related skills; every score comes from the same FSRS standard.
| Skill | FS score | Stars | Last updated | License |
|---|---|---|---|---|
| Academic Figure Prompt — Modern ML Airy Style this page | 68 · Recommended | ★ 2.6k | 7mo ago | MIT |
| Academic Figure Prompt Generator | 69 · Recommended | ★ 2.6k | 7mo ago | MIT |
| Banana Claude — Gemini Image Creative Director | 59 · Recommended | ★ 1.1k | 7d ago | MIT |
| Codex Image Generation Skill (imagegen) ✓ OpenAI · Official | 56 · Use with care | ★ 129k | 11d ago | Apache-2.0 |
| GPT Image 2 Creative Workflow | 53 · Use with care | ★ 13k | 15d ago | MIT |
How did FollowSkills review this skill?
Generates prompts for AI image tools to produce academic figures — a pure text-generation task, with rules stated as validated across 7 iterations, no execution risk.
Open a dimension to read why it scored that way
Evidence confidence：Low — Mostly static review, author material or a limited demo; useful for discovery, not high-risk decisions.
This review was completed under FSRS 1.0. Dimension scores are not converted; it is queued for re-review under FSRS 2.0.
See the full review method →