by alirezarezvani
senior-data-scientist is a Claude skill for A/B test design, causal reasoning, feature engineering, and tabular ML evaluation. Use it to guide sample sizing, metric choice, leakage checks, SHAP review, and MLflow-style tracking; scripts are scaffold templates, not complete engines.
by phuryn
Perform cohort-analysis on user retention, engagement decay, and feature adoption by cohort. This cohort-analysis skill is built for Data Analysis workflows that need validation, calculation, visualization, and clear insights from structured user behavior data.
by mukul975
detecting-beaconing-patterns-with-zeek helps analyze Zeek conn.log intervals to detect C2-style beaconing. It uses ZAT, groups flows by source, destination, and port, and scores low-jitter patterns with statistical checks. Ideal for SOC, threat hunting, incident response, and detecting-beaconing-patterns-with-zeek for Security Audit workflows.
by mukul975
analyzing-api-gateway-access-logs helps parse API Gateway access logs to detect BOLA/IDOR, rate-limit bypass, credential scanning, and injection attempts. Built for SOC triage, threat hunting, and Security Audit workflows across AWS API Gateway, Kong, and Nginx-style logs using pandas-based analysis.
by K-Dense-AI
Seaborn is a seaborn skill for Python statistical visualization with pandas-friendly inputs and strong defaults. Use it for quick exploration of distributions, relationships, categorical comparisons, box plots, violin plots, pair plots, and heatmaps. Built on matplotlib for static, publication-ready charts.
by K-Dense-AI
scikit-learn helps you build classical machine learning workflows in Python. Use this scikit-learn skill for classification, regression, clustering, preprocessing, model evaluation, hyperparameter tuning, and pipelines. It’s a practical scikit-learn guide for tabular data and repeatable model development.
by K-Dense-AI
pydeseq2 is a Python DESeq2 skill for bulk RNA-seq differential gene expression analysis. Use it to compare conditions, fit single- or multi-factor designs, apply Wald tests and FDR correction, and generate volcano or MA plots in pandas and AnnData workflows.
by K-Dense-AI
geopandas skill for Python geospatial vector data analysis, including shapefiles, GeoJSON, and GeoPackage files. Use it to read, clean, join, buffer, clip, reproject, and export spatial data with less guesswork.
by ClickHouse
chdb-datastore is a pandas-compatible skill for fast data analysis with a ClickHouse-backed DataStore API. It supports file, database, and cloud connectors, cross-source joins, and minimal code changes for pandas-style workflows. Use this chdb-datastore guide when you want a drop-in analysis layer for larger datasets.
