By K-Dense-AI
Accelerate scientific research and engineering workflows with 150+ ready-to-use agent skills spanning bioinformatics, cheminformatics, quantum computing, clinical documentation, literature review, statistical analysis, and ML model development across domains.
Search scientific papers and retrieve structured experimental data extracted from full-text studies via the BGPT MCP server. Returns 25+ fields per paper including methods, results, sample sizes, quality scores, and conclusions. Use for literature reviews, evidence synthesis, and finding experimental details not available in abstracts alone.
Use when working directly with the `esm` Python SDK, ESM3 or ESMC model IDs, Forge/Biohub inference clients, or ESMFold2 folding workflows.
Phylogenetic tree toolkit (ETE). Tree manipulation (Newick/NHX), evolutionary event detection, orthology/paralogy, NCBI taxonomy, visualization (PDF/SVG), for phylogenomics.
How to use the Adaptyv Bio Foundry API and Python SDK for protein experiment design, submission, and results retrieval. Use this skill whenever the user mentions Adaptyv, Foundry API, protein binding assays, protein screening experiments, BLI/SPR assays, thermostability assays, or wants to submit protein sequences for experimental characterization. Also trigger when code imports `adaptyv`, `adaptyv_sdk`, or `FoundryClient`, or references `foundry-api-public.adaptyvbio.com`.
This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.
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🔔 Claude Scientific Skills is now Scientific Agent Skills. Same skills, broader compatibility — now works with any AI agent that supports the open Agent Skills standard, not just Claude.
New: K-Dense BYOK — A free, open-source AI co-scientist that runs on your desktop, powered by Scientific Agent Skills. Bring your own API keys, pick from 40+ models, and get a full research workspace with web search, file handling, 100+ scientific databases, and access to all 148 skills in this repo. Your data stays on your computer, and you can optionally scale to cloud compute via Modal for heavy workloads. Get started here.
Stay up to date: Follow K-Dense on X, LinkedIn, and YouTube for new skills, release announcements, walkthroughs, research workflow demos, and examples you can use with your own AI agent.
A comprehensive collection of 148 ready-to-use scientific and research skills (covering cancer genomics, drug-target binding, molecular dynamics, RNA velocity, geospatial science, time series forecasting, scientific ML resource discovery via Hugging Science, 78+ scientific databases, and more) for any AI agent that supports the open Agent Skills standard, created by K-Dense. Works with Cursor, Claude Code, Codex, Google Antigravity, and more. Transform your AI agent into a research assistant capable of executing complex multi-step scientific workflows across biology, chemistry, medicine, and beyond.
⭐ Help make AI for science easier to discover: If Scientific Agent Skills saves you time, teaches your agent a workflow, or helps your lab move faster, please star this repository. A star is a public signal that these open, reusable research skills are worth maintaining: it helps scientists, engineers, and open-source contributors find the project, shows which agent-skill standards are gaining real adoption, and gives us a clear reason to keep expanding the collection for the community.
General-purpose assistant for writing scientific papers, research, and technical documentation with academic rigor. Improves clarity and structure of scholarly work.
Computational-science methodology for Claude Code: research framing, pre-registration, reproducible analysis, anomaly investigation, and red-team review
Life sciences computational skills for scientific AI agents — 197 skills covering genomics, proteomics, drug discovery, biostatistics, scientific computing, and scientific writing
1000+ scientific tools (PubMed, UniProt, PubChem, TCGA, FAERS, ClinicalTrials.gov, etc.) + 115 research skills + MCP server + research slash commands.
Scientific writing, citations, grants, posters, and academic career (13 skills)
Three AI models, one synthesis — multi-model research workflow for scientific domains
Connect to preclinical research tools and databases (literature search, genomics analysis, target prioritization) to accelerate early-stage life sciences R&D
Autonomous research loops with 10 commands. Generalizes Karpathy's autoresearch loop to any domain with mechanical evaluation, overnight persistence, and zero dependencies.