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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.

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skills

esm

Protein language models through the EvolutionaryScale esm Python SDK. Generate and embed sequences with ESM3 (multimodal sequence, structure and function prompting), extract per-residue and mean-pooled embeddings with ESM C, fold sequences with ESMFold2, and run inference locally or against the Forge and Biohub hosted clients. Use this skill for protein representation learning, variant effect and mutational scanning from likelihoods, sequence generation and inpainting, structure prediction from sequence alone, and embedding features for downstream models. Also trigger on esm, ESM3, ESMC, ESM Cambrian, ESMFold2, from esm.models, ESMProtein, GenerationConfig, forge.evolutionaryscale.ai, biohub.ai, or ESM_API_KEY.

Version
1.2
License
MIT
Compatibility
Requires Python >=3.12,<3.13 and `esm` 3.2.3 from PyPI. Local ESM3-open inference needs a GPU with roughly 16 GB of memory and a gated Hugging Face licence acceptance; hosted inference through Forge or Biohub needs an API key in ESM_API_KEY and no local GPU. ESMFold2 is served through Biohub rather than the local SDK.
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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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