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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.

depmap

Query the Cancer Dependency Map (DepMap) for cancer cell line gene dependency scores (CRISPR Chronos), RNAi DEMETER2 scores, PRISM compound sensitivity, and gene effect profiles across the cell-line panel. Use for identifying cancer-selective vulnerabilities, separating pan-essential genes from selective ones, finding synthetic lethal interactions, correlating dependency with mutation, expression and copy number, and validating oncology drug targets. Also trigger on DepMap, Chronos gene effect, CRISPRGeneEffect.csv, DEMETER2, PRISM repurposing, co-essentiality, pan-essential, or ACH- cell line identifiers.

Version
1.1
License
MIT
Compatibility
Requires Python 3.10+ with pandas, numpy, scipy and requests. Analysis is download-based — the DepMap release files (CRISPRGeneEffect.csv is roughly 500 MB) are fetched from the portal by hand and read locally. The portal gates programmatic access behind a browser verification page, so there is no usable REST API. Data is CC-BY-4.0 and requires registration to download.
Read SKILL.md at the source

Pinned to revision f67572246d9b, so it is the text this page describes rather than whatever the author pushed since.

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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