By kellsaro
Accelerate scientific research with 148 skills spanning bioinformatics, cheminformatics, quantum computing, ML, data analysis, lab automation, literature review, and grant writing
Automated LLM-driven hypothesis generation and testing on tabular datasets. Use when you want to systematically explore hypotheses about patterns in empirical data (e.g., deception detection, content analysis). Combines literature insights with data-driven hypothesis testing. For manual hypothesis formulation use hypothesis-generation; for creative ideation use scientific-brainstorming.
Cloud laboratory platform for automated protein testing and validation. Use when designing proteins and needing experimental validation including binding assays, expression testing, thermostability measurements, enzyme activity assays, or protein sequence optimization. Also use for submitting experiments via API, tracking experiment status, downloading results, optimizing protein sequences for better expression using computational tools (NetSolP, SoluProt, SolubleMPNN, ESM), or managing protein design workflows with wet-lab validation.
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.
Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for population-scale queries use cellxgene-census.
Infer gene regulatory networks (GRNs) from gene expression data using scalable algorithms (GRNBoost2, GENIE3). Use when analyzing transcriptomics data (bulk RNA-seq, single-cell RNA-seq) to identify transcription factor-target gene relationships and regulatory interactions. Supports distributed computation for large-scale datasets.
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A comprehensive collection of 146+ ready-to-use scientific and research skills (now including financial/SEC research, U.S. Treasury fiscal data, OFR Hedge Fund Monitor, and Alpha Vantage market data) for any AI agent that supports the open Agent Skills standard, created by K-Dense. Works with Cursor, Claude Code, Codex, and more. Transform your AI agent into a research assistant capable of executing complex multi-step scientific workflows across biology, chemistry, medicine, and beyond.
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Want 10x the power with zero setup? K-Dense Web is the complete AI co-scientist platform—everything in this repo, plus:
| Feature | This Repo | K-Dense Web |
|---|---|---|
| Scientific Skills | 140 skills | 200+ skills (exclusive access) |
| Setup Required | Manual installation | Zero setup — works instantly |
| Compute | Your machine | Cloud GPUs & HPC included |
| Workflows | Basic prompts | End-to-end research pipelines |
| Outputs | Code & analysis | Publication-ready figures, reports & papers |
| Integrations | Local tools | Lab systems, ELNs, cloud storage |
Researchers at Stanford, MIT, and leading pharma companies use K-Dense Web to accelerate discoveries.
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These skills enable your AI agent to seamlessly work with specialized scientific libraries, databases, and tools across multiple scientific domains:
Ready-to-use agent skills for research, science, engineering, analysis, finance, and technical writing across domains.
Tool for retrieving and analyzing biological or sequential data from ToolUniverse.
Life sciences computational skills for scientific AI agents — 197 skills covering genomics, proteomics, drug discovery, biostatistics, scientific computing, and scientific writing
Scientific writing, citations, grants, posters, and academic career (13 skills)
Connect to preclinical research tools and databases (literature search, genomics analysis, target prioritization) to accelerate early-stage life sciences R&D
Access ClinicalTrials.gov data. The Clinical Trials Connector gives Claude access to ClinicalTrials.gov, the NIH/NLM registry of FDA-regulated clinical studies conducted worldwide.