PaperBanana Skills for Claude Code

One sentence in, publication-quality academic figure out.
Powered by a 5-agent pipeline that plans, styles, generates, and self-critiques your illustrations.

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Gallery

Biology — Signal Pathway	NLP — RAG Pipeline
Data Engineering — Lakehouse	Medical AI — U-Net + Mamba

All figures generated from plain text descriptions — zero manual drawing.

Transformer Architecture	Mamba SSM Architecture
RAG Pipeline

Skills in this Marketplace

Feature Matrix

What's New in v4.0

Eval-First Quality System

A 6-item binary checklist evaluator that measures academic figure quality without human reference images:

Baseline: 76% → 100% after prompt optimization. Color restraint was the bottleneck (33% → 100%).

Autoresearch Self-Optimization

Automated prompt mutation loop inspired by Karpathy's autoresearch:

Mutate prompt → Generate figures → Evaluate checklist → Keep or Revert → Repeat

• One mutation per round (isolation principle)
• Targets weakest checklist dimension automatically
• Versioned prompt snapshots + JSONL changelog
• Stop condition: 3 consecutive rounds at 90%+ or 20 rounds max

Multi-Venue Academic Styles

/paperbanana generate method.txt "Architecture overview" --venue neurips

Built-in style guides for NeurIPS, ICML, ACL, IEEE — each with venue-specific color palettes, layout conventions, and typography.

Robust Error Handling

Quick Start

# 1. Install PaperBanana
git clone https://github.com/llmsresearch/paperbanana.git
cd paperbanana && pip install -e ".[google]"

# 2. Add the marketplace & install skills
claude plugin marketplace add PlutoLei/paperbanana-skill
claude plugin install paperbanana@paperbanana-skills
claude plugin install paperbanana-slide-deck@paperbanana-skills --scope project  # optional

# 3. Generate your first figure
# /paperbanana A 4-layer CNN with batch normalization for image classification

Note: This repository contains Claude Code skill definitions (SKILL.md files). The underlying Python package lives at llmsresearch/paperbanana.

Why PaperBanana?

Pipeline Architecture

The pipeline runs iteratively: the Critic evaluates each output against academic quality criteria and either accepts it or sends revision instructions back to the Planner. Parse failures are handled safely — never silently approved.

Slide Deck Orchestrator

End-to-end presentation creation: analyze content → select from 23 visual styles → generate outlines → batch-generate 4K slides → merge to PPTX/PDF.

Commands

# Generate with venue-specific style
/paperbanana generate method.txt "Overview of the proposed framework" --venue neurips --optimize

# Generate from PDF
/paperbanana generate paper.pdf "Architecture diagram" --pages 3-5

# Auto-refine until Critic is satisfied
/paperbanana generate method.txt "Pipeline overview" --auto

# Continue with feedback
/paperbanana generate --continue --feedback "Make the arrows thicker and add color coding"

# Custom provider and aspect ratio
/paperbanana generate method.txt "Wide pipeline" --vlm-provider anthropic --aspect-ratio 16:9

# Batch generate slides with style
/paperbanana slide-batch prompts/ --resolution 4k --style ml-ai --iterations 3

Supported Providers

Retry policy: Transient errors (429, 5xx) retry with exponential backoff. Auth errors (401, 403) fail immediately — no wasted retries.

Installation

Option A: Plugin marketplace (recommended)

claude plugin marketplace add PlutoLei/paperbanana-skill
claude plugin install paperbanana@paperbanana-skills
claude plugin install paperbanana-slide-deck@paperbanana-skills --scope project  # optional

Option B: Manual install

# paperbanana skill (user-level)
mkdir -p ~/.claude/skills/paperbanana
curl -o ~/.claude/skills/paperbanana/SKILL.md \
  https://raw.githubusercontent.com/PlutoLei/paperbanana-skill/master/plugins/paperbanana/skills/paperbanana/SKILL.md

# paperbanana-slide-deck skill (project-level, optional)
mkdir -p .claude/skills/paperbanana-slide-deck
curl -o .claude/skills/paperbanana-slide-deck/SKILL.md \
  https://raw.githubusercontent.com/PlutoLei/paperbanana-skill/master/plugins/paperbanana-slide-deck/skills/paperbanana-slide-deck/SKILL.md

PaperBanana package setup

git clone https://github.com/llmsresearch/paperbanana.git
cd paperbanana
pip install -e ".[google]"          # Gemini (default, free tier available)
# pip install -e ".[all]"           # All providers
python -m paperbanana.cli setup     # Interactive API key configuration

Style Presets (23 available)

Use --style <name> with slide or slide-batch.

Evaluation Infrastructure

PaperBanana v4.0 includes a complete evaluation system for measuring and improving figure quality:

evaluation/
├── checklist.py          # 6-item binary pass/fail evaluator
├── judge.py              # VLM-as-Judge comparative evaluation
├── benchmark.py          # End-to-end benchmark harness
└── prompt_ablation.py    # A/B prompt comparison runner

scripts/
├── run_checklist_baseline.py   # Run checklist on existing outputs
└── autoresearch_loop.py        # Automated prompt optimization

Run your own baseline:

python scripts/run_checklist_baseline.py --output-dir outputs/ --report baseline.json

Run autoresearch optimization:

python scripts/autoresearch_loop.py --test-inputs data/checklist_test_set --max-rounds 10 --target 90

Troubleshooting

Contributing

Contributions welcome! See the Contributing Guide.

License

MIT