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Provides code, pretrained weights, and tooling for protein language models and structure prediction — including ESMC, ESMFold2, sparse autoencoders (SAEs), and the ESM Atlas. Includes model checkpoints, tutorials, Hugging Face & Biohub integration, and an MIT license.

High-accuracy biomolecular structure prediction suite: open-source models (protenix-v2/v1), a benchmark/evaluation toolkit, and a web server for inference. Targets protein/antibody–antigen and ligand-aware predictions with inference-time sampling and constraint support.

Provides 134 ready-to-use Agent Skills that let AI agents execute multi-step scientific workflows (bioinformatics, cheminformatics, imaging, clinical research). Each skill includes curated docs and examples plus unified access to 100+ scientific databases and common Python packages — for agents that support the Agent Skills standard.

Provides 170+ ready-to-use scientific skills that extend an LLM/agent (e.g., Claude/Claude Code) to run multi-step scientific workflows — includes curated SKILL.md docs, examples, and integrations with 250+ databases and common Python scientific libraries.([github.com](https://github.com/K-Dense-AI/claude-scientific-skills))

Benchmarks LLM and VLM capabilities for toxicity-aware molecular editing using toxicity‑cliff molecule pairs. It provides QA-formatted tasks and CSV splits for fragment identification, non-toxic fragment generation, and detoxified molecule generation—useful for safety evaluation and drug-discovery research.