kakashi-ventures/magellan-cli
Autonomous AI experiment in cross-disciplinary scientific discovery. Can a multi-agent system autonomously find real scientific connections that humans haven't made yet? This project tests that question.
This project helps scientists autonomously find new, testable hypotheses and scientific connections, especially in life sciences. You provide a general command like "/discover" or specific areas of interest (e.g., "circadian biology x tumor immune evasion"), and it outputs hypothesis cards with supporting evidence and cross-model validation reports. Researchers, biologists, or medical scientists who want to explore untapped connections in scientific literature without extensive manual search would use this.
Use this if you are a life scientist looking to rapidly generate novel, testable hypotheses and discover latent links across different scientific domains with minimal manual effort.
Not ideal if you need human-in-the-loop control at every step of hypothesis generation or if your primary domain is outside of life sciences, as scoring weights are optimized for that field.
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12
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Language
TeX
License
Apache-2.0
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Last pushed
Apr 03, 2026
Commits (30d)
0
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