--> --- name: paper-banana description: Agentic framework for automating the generation of publication-ready academic illustrations and statistical plots. license: CC-BY-SA-4.0 metadata: author: Peking University & Google Cloud AI Research version: "1.0.0" compatibility: - system: Python 3.9+ allowed-tools: - run_shell_command - read_file measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. --- PaperBanana is an advanced agentic framework designed to au...
Scanned 9/8/2026
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---
name: paper-banana
description: Agentic framework for automating the generation of publication-ready academic illustrations and statistical plots.
license: CC-BY-SA-4.0
metadata:
author: Peking University & Google Cloud AI Research
version: "1.0.0"
compatibility:
- system: Python 3.9+
allowed-tools:
- run_shell_command
- read_file
measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes.
---
# PaperBanana
PaperBanana is an advanced agentic framework designed to automate the creation of high-quality, publication-ready academic illustrations. It employs a multi-agent architecture to retrieve data, plan visualizations, style figures, and critique the output, ensuring adherence to strict academic standards.
## When to Use This Skill
- You need to generate methodology diagrams from text descriptions.
- You want to create statistical plots (e.g., bar charts, line graphs, scatter plots) that meet academic publication standards.
- You need to refine existing figures for better clarity, aesthetics, or faithfulness to the data.
## Core Capabilities
1. **Multi-Agent Orchestration**: Coordinates specialized agents (Retriever, Planner, Stylist, Visualizer, Critic) to handle complex illustration tasks.
2. **Methodology Diagrams**: Generates flowcharts and system architecture diagrams.
3. **Statistical Plots**: Produces high-quality plots for data visualization.
4. **Iterative Refinement**: Uses a critic agent to review and improve figures based on academic criteria.
## Workflow
1. **Input**: Provide a description of the figure or data to be visualized.
2. **Planning**: The Planner agent breaks down the request into actionable steps.
3. **Generation**: The Visualizer and Stylist agents create the initial draft.
4. **Critique & Refine**: The Critic agent reviews the output, and the system iteratively improves it.
5. **Output**: A high-resolution image file ready for inclusion in a manuscript.
## References
- [Project Website](https://paperbanana.github.io/) (Placeholder based on typical project structure)
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