Explore and document PaperBanana academic illustration tool
Session from traceweave on Hugging Face by Samarth0710 · MIT · condensed by Coders Talk
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1msession
0interventions
GOAL
Understand the PaperBanana tool's architecture, configuration, and usage patterns well enough to know exactly how to invoke it for generating academic paper figures.
- +0Prompt · +0Thoroughly explore the paperbanana tool: read README, paperbanana.py, config.py, app.py, examples.py, agents/, aesthetic_guidelines.py, examples/, scripts/, figure generation method, and full CLI/API usage.
- +0mAgent did · +0mListed directory structure and located all key python, markdown and config files in the paperbanana repo.
- +0mAgent did · +0mRead README.md, paperbanana.py, config.py, app.py, examples.py, aesthetic_guidelines.py and utils.py to understand the tool's purpose and 5-agent pipeline (Retriever, Planner, Stylist, Visualizer, Critic).
- +0mAgent did · +0mRead all agent implementation files (retriever, planner, stylist, visualizer, critic) to understand how each stage of the pipeline works.
- +0mAgent did · +0mExplored scripts/ and examples/ directories, read generate_self_diagram.py, load_reference_set.py and requirements.txt to see real usage patterns and dependencies.
- +0mAgent did · +0mChecked pyproject.toml, .env, the JSON reference dataset, and the docs/paperbanana.md paper writeup to round out configuration and background details.
- +1mOutcome · +1mProduced a comprehensive summary covering what the tool does, its 5-agent pipeline, configuration, CLI/API usage, and figure generation approach.
VERDICT
I'd start with the same broad 'read everything and summarize' prompt next time since this was a pure exploration task with no code changes needed. The agent worked through it systematically file by file without any wrong turns, so there was nothing for me to correct here.