by K-Dense-AI
Open Notebook is a self-hosted, open-source research workspace for document analysis, notes, chat with sources, search, and podcast-style summaries. Use the open-notebook skill to organize notebooks, ingest PDFs, web pages, audio, video, and Office files, and support private, API-first workflows for Data Analysis.
by K-Dense-AI
histolab is a Python skill for whole-slide image preprocessing in digital pathology. It supports tissue detection, tile extraction, and stain normalization for H&E slides, making it useful for dataset prep, quick tile-based analysis, and lightweight data analysis workflows. Install and use histolab with practical guidance on masks, tilers, and slide management.
by K-Dense-AI
The statsmodels skill helps you use statsmodels for data analysis in Python when you need statistical models, inference, and diagnostics. It fits OLS, GLM, discrete outcomes, time series, and mixed models, with coefficient tables, p-values, confidence intervals, and assumption checks. Use this statsmodels guide for econometrics, forecasting, and defensible reporting.
by K-Dense-AI
The statistical-analysis skill helps you choose, run, and report defensible tests for Data Analysis, including assumptions, effect sizes, power, and APA-style results. Use it for academic research, experiments, and observational studies when test selection and clear reporting matter more than coding a specific model.
by K-Dense-AI
scanpy skill for single-cell RNA-seq data analysis in Python. Use it for QC, normalization, PCA, UMAP/t-SNE, clustering, marker gene discovery, trajectory analysis, and publication-quality plots. Best for exploratory scRNA-seq workflows built around AnnData, with clear scanpy usage and install guidance.
by K-Dense-AI
matplotlib skill for Python plotting with full control over axes, labels, legends, layouts, and export formats. Use it for scientific figures, multi-panel analyses, custom chart types, and reproducible visualizations when you need more precision than a generic chart prompt. It is a strong matplotlib guide for Data Analysis and publication-ready plots.
by K-Dense-AI
The matlab skill helps you generate, debug, and adapt MATLAB or GNU Octave code for matrix operations, data analysis, visualization, statistics, optimization, and scientific computing. Use it for runnable MATLAB usage, MATLAB for Data Analysis, MATLAB-to-Python translation, or Octave-compatible scripts when you need less trial-and-error than a generic prompt.
by K-Dense-AI
labarchive-integration helps with LabArchives REST API workflows for notebook access, entries, attachments, backups, reports, and integrations with Protocols.io, Jupyter, and REDCap. Use this labarchive-integration skill for API Development when you need practical guidance on credentials, configuration, and repeatable ELN automation.
by K-Dense-AI
imaging-data-commons helps you query and download public cancer imaging data from NCI Imaging Data Commons with idc-index. Use it for imaging-data-commons usage across CT, MR, PET, and pathology datasets, including metadata search, browser preview, licensing checks, and AI training or data analysis workflows. No authentication required.
by K-Dense-AI
gget is a bioinformatics skill for fast, unified access to 20+ genomic databases and analysis tools from CLI or Python. Use it for gene info, BLAST-related lookups, AlphaFold structures, expression data, disease associations, and enrichment-style analysis. It suits quick exploration and gget for Data Analysis workflows.
by K-Dense-AI
The exploratory-data-analysis skill turns scientific files into format-aware EDA reports. It detects file type, summarizes structure and quality, extracts key metadata, and suggests downstream analysis. Use it for exploratory-data-analysis for Data Analysis across chemistry, bioinformatics, microscopy, spectroscopy, proteomics, metabolomics, and other scientific file formats.
by K-Dense-AI
astropy is a Python toolkit for astronomy and astrophysics workflows. Use this astropy skill for celestial coordinates, units, FITS files, time scales, tables, WCS, cosmology, and astropy for Data Analysis. It helps with practical astronomy tasks like coordinate transforms, unit conversion, and data processing.
by openai
The jupyter-notebook skill helps you create, refactor, and structure .ipynb notebooks for experiments, tutorials, and data analysis. It uses bundled templates and the new_notebook.py helper to produce clean, reproducible notebooks with clear sections, runnable cells, and fewer JSON mistakes.
