Инструменты

166 research skills maintained by K-Dense (formerly Claude Scientific Skills), spanning bioinformatics, cheminformatics, clinical research, materials and physics, including unified access to 78 public databases such as PubChem and UniProt. Works with Claude Code, Codex and Cursor.

Teaches agents standard single-cell RNA-seq analysis with Scanpy: QC, normalization, PCA/UMAP, clustering, differential expression and plots, with ready-to-run pipeline scripts and guidance on converting Seurat and other R objects to h5ad. Needs Python 3.12+; by K-Dense.

Guides agents to the right statistical method for research data: t-tests, ANOVA, chi-square, regression and Bayesian analysis, checking assumptions, computing effect sizes and power, and reporting results in APA format. Python-based (pingouin, statsmodels); by K-Dense.

Publishes SQLite databases as browsable, queryable web pages and JSON APIs, with SQL queries, metadata and plugins, and deploys to Cloud Run and other platforms with datasette publish. Great for data exploration and data journalism. Needs Python 3.10+.

Terminal tool for exploring and wrangling tabular data: opens dozens of formats including CSV, JSON, Excel and SQLite for filtering, sorting, pivots and frequency counts. --batch mode replays actions headlessly or converts file formats.

Creates, edits and validates reproducible Python and SQL Jupyter notebooks: organizes cells as reports or tutorials, checks conclusions against actual output and reruns top to bottom before handoff. Maintained by OpenAI in the Data Analytics plugin of openai/plugins.

Veteran suite of CSV command-line tools: in2csv converts Excel and JSON to CSV, csvcut, csvgrep and csvsort filter and sort, csvstat computes statistics, and csvsql runs SQL directly against CSV files.

Connects agents to live Jupyter notebooks: read, write, insert and execute cells and read multimodal outputs like charts, for interactive data analysis. Bring your own JupyterLab or JupyterHub; open source, maintained by Datalayer.