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k-dense-ai/drug-discovery-agent-skills

v1.3.0MIT

Agent Skills for small-molecule and protein therapeutics: target validation and human genetics, bioactivity and chemical space, generative design and retrosynthesis, docking, free energy and dynamics, ADMET and PK translation, protein, antibody, degrader and oligonucleotide design, and the clinical and regulatory record.

retrosynthesis

Plan synthetic routes and judge whether a proposed molecule can actually be made, using AiZynthFinder's Monte-Carlo tree search over template-derived reactions and a purchasable building-block stock. Use this skill to configure expansion and filter policies, choose a stock file, run route search over a candidate set, and read the returned trees — solved fraction, route depth, and which building blocks a route bottoms out in. Also trigger on AiZynthFinder, retrosynthetic tree search, synthetic accessibility, SAscore, RAscore, building-block stock, reaction template, or route scoring.

Version
1.0
License
MIT
Compatibility
Requires Python 3.10+. The bundled scripts write AiZynthFinder YAML configuration and parse its route JSON using only the standard library. Running a search needs aizynthfinder 4.4+ (pip, Python >=3.10 and <3.13, MIT) plus its downloaded policy models and a stock file; CPU is sufficient, though a GPU speeds up the expansion policy.
Read SKILL.md at the source

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Pre-approved tools experimental

Experimental field. Support varies between clients, so this list is what the author declared, not what your client will enforce.

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