paper-illustration

name paper-illustration description Generate publication-quality AI illustrations for academic papers using Gemini image generation. Creates architecture diagrams, method illustrations with Claude-supervised iterative refinement loop. Use when user says "生成图表", "画架构图", "AI绘图", "paper illustration", "generate diagram", or needs visual figures for papers. argument-hint [description-or-method-file] [— style-ref: <source>] allowed-tools Bash(*), Read, Write, Edit, Grep, Glob, mcp__codex__codex, mcp__codex__codex-reply, WebSearch Paper Illustration: Multi-Stage Claude-Supervised Figure Generation Generate publication-quality illustrations using a multi-stage workflow with Claude as the STRICT supervisor/reviewer . Core Design Philosophy ┌──────────────────────────────────────────────────────────────────────────┐ │ MULTI-STAGE ITERATIVE WORKFLOW │ ├──────────────────────────────────────────────────────────────────────────┤ │ │ │ User Request │ │ │ │ │ ▼ │ │ ┌─────────────┐ │ │ │ Claude │ ◄─── Step 1: Parse request, create initial prompt │ │ │ (Planner) │ │ │ └──────┬──────┘ │ │ │ │ │ ▼ │ │ ┌─────────────┐ │ │ │ Gemini │ ◄─── Step 2: Optimize layout description │ │ │ (gemini-3-pro)│ - Refine component positioning │ │ │ Layout │ - Optimize spacing and grouping │ │ └──────┬──────┘ │ │ │ │ │ ▼ │ │ ┌─────────────┐ │ │ │ Gemini │ ◄─── Step 3: CVPR/NeurIPS style verification │ │ │ (gemini-3-pro)│ - Check color palette compliance │ │ │ Style │ - Verify arrow and font standards │ │ └──────┬──────┘ │ │ │ │ │ ▼ │ │ ┌─────────────┐ │ │ │ Paperbanana │ ◄─── Step 4: Render final image │ │ │ (gemini-3- │ - High-quality image generation │ │ │ pro-image) │ - Internal codename: Nano Banana Pro │ │ └──────┬──────┘ │ │ │ │ │ ▼ │ │ ┌─────────────┐ │ │ │ Claude │ ◄─── Step 5: STRICT visual review + SCORE (1-10) │ │ │ (Reviewer) │ - Verify EVERY arrow direction │ │ │ STRICT! │ - Verify EVERY block content │ │ └──────┬──────┘ - Verify aesthetics & visual appeal │ │ │ │ │ ▼ │ │ Score ≥ 9? ──YES──► Accept & Output │ │ │ │ │ NO │ │ │ │ │ ▼ │ │ Generate SPECIFIC improvement feedback ──► Loop back to Step 2 │ │ │ └──────────────────────────────────────────────────────────────────────────┘ Constants IMAGE_MODEL = gemini-3-pro-image-preview — Paperbanana (Nano Banana Pro) for image rendering REASONING_MODEL = gemini-3-pro-preview — Gemini for layout optimization and style checking MAX_ITERATIONS = 5 — Maximum refinement rounds TARGET_SCORE = 9 — Minimum acceptable score (1-10) — RAISED FOR QUALITY OUTPUT_DIR = figures/ai_generated/ — Output directory API_KEY_ENV = GEMINI_API_KEY — Environment variable Optional: Style reference ( — style-ref: <source> , opt-in) Lets the user steer structural figure conventions (caption length, panel-count distribution, figure-to-table ratio in the parent paper) toward a reference paper. Default OFF — when the user does not pass — style-ref , do nothing differently from before. Only when — style-ref: <source> appears in $ARGUMENTS , run the helper FIRST, before generating prompts: # Resolve $STYLE_HELPER via the canonical strict-safe chain (see # shared-references/integration-contract.md §2). Policy A — gate: # unresolved helper means --style-ref cannot be satisfied, so abort. cd " $(git rev-parse --show-toplevel 2>/dev/null || pwd) " || exit 1 if [ -z " ${ARIS_REPO:-} " ] && [ -f .aris/installed-skills.txt ]; then ARIS_REPO=$(awk -F '\t' '$1=="repo_root"{print $2; exit}' .aris/installed-skills.txt 2>/dev/null) || true fi if [ -z " ${ARIS_REPO:-} " ] && [ -f " $HOME /.aris/repo" ]; then ARIS_REPO=$( cat " $HOME /.aris/repo" 2>/dev/null) || true fi STYLE_HELPER= ".aris/tools/extract_paper_style.py" [ -f " $STYLE_HELPER " ] || STYLE_HELPER= "tools/extract_paper_style.py" [ -f " $STYLE_HELPER " ] || { [ -n " ${ARIS_REPO:-} " ] && STYLE_HELPER= " $ARIS_REPO /tools/extract_paper_style.py" ; } [ -f " $STYLE_HELPER " ] || { echo "ERROR: extract_paper_style.py not resolved at .aris/tools/, tools/, \$ARIS_REPO/tools/, or via ~/.aris/repo." >&2 echo " Fix: rerun bash tools/install_aris.sh or smart_update.sh (refreshes ~/.aris/repo), export ARIS_REPO, or copy the helper to tools/." >&2 echo " --style-ref cannot be satisfied; aborting." >&2 exit 1 } STYLE_STATUS=0 CACHE=$(python3 " $STYLE_HELPER " -- source "<source>" ) || STYLE_STATUS=$? case " $STYLE_STATUS " in 0) ;; # use $CACHE/style_profile.md as structural guidance 2) echo "warning: style-ref skipped (missing optional dep)" >&2 ;; 3) echo "error: --style-ref source failed; aborting illustration" >&2 ; exit 1 ;; *) echo "error: helper failed unexpectedly; aborting illustration" >&2 ; exit 1 ;; esac Sources accepted: local TeX dir / file, local PDF, arXiv id, http(s) URL. Overleaf URLs/IDs are rejected — clone via /overleaf-sync setup <id> first and pass the local clone path. Strict rules (full contract in tools/extract_paper_style.py docstring): Use style_profile.md to align caption length and figure density with the reference paper. The CVPR/ICLR/NeurIPS visual standards above still take precedence — --style-ref only refines length-and-density tendencies, never image content. Never copy figure content, color palettes, or specific design elements from anything reachable through the cache. The visual design comes from the user's prompt, not the reference. Never pass — style-ref (or the cache contents) to the Claude vision-checker / Gemini reasoning-checker sub-agents when they score the generated image — the image must be judged on its own merits. CVPR/ICLR/NeurIPS Top-Tier Conference Style Guide What "CVPR Style" Actually Means: Visual Standards Clean white background — No decorative patterns or gradients (unless subtle) Sans-serif fonts — Arial, Helvetica, or Computer Modern; minimum 14pt Subtle color palette — Not rainbow colors; use 3-5 coordinated colors Print-friendly — Must be readable in grayscale (many reviewers print papers) Professional borders — Thin (2-3px), solid colors, not flashy Layout Standards Horizontal flow — Left-to-right is the standard for pipelines Clear grouping — Use subtle background boxes to group related modules Consistent sizing — Similar components should have similar sizes Balanced whitespace — Not cramped, not sparse Arrow Standards (MOST CRITICAL) Thick strokes — 4-6px minimum (thin arrows disappear when printed) Clear arrowheads — Large, filled triangular heads Dark colors — Black or dark gray (#333333); avoid colored arrows Labeled — Every arrow should indicate what data flows through it No crossings — Reorganize layout to avoid arrow crossings CORRECT DIRECTION — Arrows must point to the RIGHT target! Visual Appeal (科研风格 - Professional Academic Style) 目标：既不保守也不花哨，找到平衡点 ✅ 应该有的视觉元素： Subtle gradient fills — 淡雅的渐变填充（同色系从浅到深），不是炫彩 Rounded corners — 圆角矩形（6-10px radius），现代感但不夸张 Clear visual hierarchy — 通过大小、颜色深浅区分层次 Consistent color coding — 统一的配色方案（3-4种主色） Internal structure — 大模块内部显示子组件（如Encoder内部的layer结构） Professional typography — 清晰的标签，适当的字号层次 ✅ 配色建议（学术专业）： Inputs : 柔和的绿色系 (#10B981 / #34D399) Encoders : 专业的蓝色系 (#2563EB / #3B82F6) Fusion : 优雅的紫色系 (#7C3AED / #8B5CF6) Outputs : 温暖的橙色系 (#EA580C / #F97316) Arrows : 黑色或深灰 (#333333 / #1F2937) Background : 纯白 (#FFFFFF)，不要花纹 ❌ 要避免的过度装饰： ❌ Rainbow color schemes (彩虹配色) ❌ Heavy drop shadows (重阴影效果) ❌ 3D effects / perspective (3D透视) ❌ Excessive gradients (夸张的多色渐变) ❌ Clip art / cartoon icons (卡通图标) ❌ Decorative patterns in background (背景花纹) ❌ Glowing effects (发光效果) ❌ Too many small icons (过多小图标) ✓ 理想的视觉效果： 一眼看上去 专业、清晰 有 适度的视觉吸引力 ，但不抢眼 符合 CVPR/NeurIPS论文 的审美标准 打印友好 （灰度模式下也能清晰辨认） 像 精心设计 的学术图表，而不是PPT模板 What to AVOID (CRITICAL) ❌ Rainbow color schemes (too many colors) ❌ Thin, hairline arrows (arrows must be THICK) ❌ Unlabeled connections ❌ Plain boring rectangles (add some visual interest) ❌ Over-decorated with shadows/glows/icons (too flashy) ❌ Small text that's unreadable when printed ❌ WRONG arrow directions — This is UNACCEPTABLE! Scope Figure Type Quality Examples Architecture diagrams Excellent Model architecture, pipeline, encoder-decoder Method illustrations Excellent Conceptual diagrams, algorithm flowcharts Conceptual figures Good Comparison diagrams, taxonomy trees Not for: Statistical plots (use /paper-figure ), photo-realistic images Workflow: MUST EXECUTE ALL STEPS Step 0: Pre-flight Check # Check API key if [ -z " $GEMINI_API_KEY " ]; then echo "ERROR: GEMINI_API_KEY not set" echo "Get your key from: https://aistudio.google.com/app/apikey" echo "Set it: export GEMINI_API_KEY='your-key'" exit 1 fi # Create output directory mkdir -p figures/ai_generated Step 1: Claude Plans the Figure (YOU ARE HERE) CRITICAL: Claude must first analyze the user's request and create a detailed prompt. Parse the input: $ARGUMENTS Claude's task: Understand what figure the user wants Identify all components, connections, data flow Create a detailed, structured prompt for Gemini Include style requirements AND visual appeal requirements Prompt Template for Claude to generate: Create a PROFESSIONAL, VISUALLY APPEALING publication-quality academic diagram following CVPR/ICLR/NeurIPS standards. ## Visual Style: 科研风格 (Academic Professional Style) ### 目标：平衡 — 既不保守也不花哨 #### DO (应该有): - **Subtle gradients** — 同色系淡雅渐变（如 #2563EB → #3B82F6），不是多色炫彩 - **Rounded corners** — 圆角矩形（6-10px），现代感 - **Clear visual hierarchy** — 通过大小、深浅区分层次 - **Internal structure** — 大模块内显示子组件结构 - **Consistent color coding** — 统一的3-4色方案 - **Professional polish** — 精致但不夸张 #### DON'T (不要有): - ❌ Rainbow/multi-color gradients (彩虹渐变) - ❌ Heavy drop shadows (重阴影) - ❌ 3D effects / perspective (3D效果) - ❌ Glowing effects (发光效果) - ❌ Excessive decorative icons (过多装饰图标) - ❌ Plain boring rectangles (完全平淡的方块) #### 理想效果： 像顶会论文中精心设计的架构图 — 专业、清晰、有适度的视觉吸引力 ## Figure Type [Architecture Diagram / Pipeline / Comparison / etc.] ## Components to Include (BE SPECIFIC ABOUT CONTENT) 1. [Component 1]: - Label: "[exact text]" - Sub-label: "[smaller text below]" - Position: [left/center/right, top/middle/bottom] - Style: [border color, fill, internal structure] 2. [Component 2]: ... ## Layout - Direction: [left-to-right / top-to-bottom] - Spacing: [tight / normal / loose] - Grouping: [how components should be grouped] ## Connections (BE EXPLICIT ABOUT DIRECTION) EXACT arrow specifications: 1. [Component A] → [Component B]: Arrow goes FROM A TO B, label it "[data type]" 2. [Component C] → [Component D]: Arrow goes FROM C TO D, label it "[data type]" ... VERIFY: Each arrow must point to the CORRECT target! ## Style Requirements (CVPR/ICLR/NeurIPS Standard) ### Visual Style - Color palette: Professional academic colors - Inputs: Green (#10B981) - Encoders: Blue (#2563EB) - Fusion modules: Purple (#7C3AED) - Outputs: Orange (#EA580C) - Font: Sans-serif (Arial/Helvetica), minimum 14pt, bold for labels - Background: Clean white, no patterns - Blocks: Rounded rectangles (8-12px radius), subtle gradient fill, colored border (2-3px) - Subtle shadows for depth effect - Print-friendly (must work in grayscale) ### CRITICAL: Arrow & Data Flow Requirements 1. **ALL arrows must be VERY THICK** - minimum 5-6px stroke width 2. **ALL arrows must have CLEAR arrowheads** - large, visible triangular heads 3. **ALL arrows must be BLACK or DARK GRAY** - not colored 4. **Label EVERY arrow** with what data flows through it 5. **VERIFY arrow direction** - each arrow MUST point to the correct target 6. **No ambiguous connections** - every arrow should have a clear source and destination ### Logic Clarity Requirements 1. **Data flow must be immediately obvious** - viewer should understand the pipeline in 5 seconds 2. **No crossing arrows** - reorganize layout to avoid arrow crossings 3. **Consistent direction** - maintain left-to-right or top-to-bottom flow throughout 4. **Group related components** - use subtle background boxes or spacing to group modules 5. **Clear hierarchy** - main components larger, sub-components smaller ## Additional Requirements [Any specific requirements from user] Step 2: Gemini Layout Optimization (gemini-3-pro) Claude sends the initial prompt to Gemini (gemini-3-pro) for layout optimization. #!/bin/bash # Step 2: Optimize layout using Gemini gemini-3-pro # This step refines component positioning and spacing set -e OUTPUT_DIR= "figures/ai_generated" mkdir -p " $OUTPUT_DIR " API_KEY= " ${GEMINI_API_KEY} " URL= "https://generativelanguage.googleapis.com/v1beta/models/gemini-3-pro-preview:generateContent?key= $API_KEY " # The initial prompt from Claude INITIAL_PROMPT= '[Claude fills in the detailed prompt here]' # Layout optimization request LAYOUT_REQUEST= "You are an expert in academic figure layout design for CVPR/NeurIPS papers. Analyze this figure request and provide an OPTIMIZED LAYOUT DESCRIPTION: $INITIAL_PROMPT Provide: 1. **Optimized Component Positions**: Exact positions (left/center/right, top/middle/bottom) for each component 2. **Spacing Recommendations**: Specific spacing between components 3. **Grouping Strategy**: Which components should be visually grouped together 4. **Arrow Routing**: Optimal paths for arrows to avoid crossings 5. **Visual Hierarchy**: Size recommendations for main vs sub-components Output a DETAILED layout specification that will be used for rendering." # Build JSON payload python3 << PYTHON import json payload = { "contents": [{"parts": [{"text": '''$LAYOUT_REQUEST'''}]}] } with open("/tmp/gemini_layout_request.json", "w") as f: json.dump(payload, f, indent=2) print("Layout request created") PYTHON # Call Gemini gemini-3-pro-preview for layout optimization (DIRECT connection, no proxy) RESPONSE=$(curl -s --max-time 90 \ -X POST " $URL " \ -H 'Content-Type: application/json' \