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Automated Data Preprocessing

preprocessing-data-with-automated-pipelines

jeremylongshore/claude-code-plugins-plus-skills

This skill builds and executes automated pipelines to clean, validate, and transform data for machine learning, covering ETL workflows, error handling, and quality reporting so Claude can deliver analysis-ready datasets.

Clustering Analysis Assistant

running-clustering-algorithms

jeremylongshore/claude-code-plugins-plus-skills

Automates clustering workflows on supplied datasets with K-means, DBSCAN, or hierarchical algorithms, handling preprocessing, validation, metrics, and visualizations to expose groupings and anomalies.

Schema Optimization Workflow Orchestrator

schema-optimization-orchestrator

jeremylongshore/claude-code-plugins-plus-skills

An advanced workflow orchestrator designed to perform multi-phase, deep-dive schema optimization on large datasets (e.g., BigQuery exports). It systematically analyzes schema structure, identifies unused or redundant fields, assesses potential impact, and generates a comprehensive, actionable report with recommended optimization strategies and estimated savings.

Dataset Splitter Tool

splitting-datasets

jeremylongshore/claude-code-plugins-plus-skills

Automates splitting datasets into training, validation, and test subsets by generating and running Python code so you can quickly prepare data for machine learning model training and evaluation.

Machine Learning Training

training-machine-learning-models

jeremylongshore/claude-code-plugins-plus-skills

Automates the end-to-end training of machine learning models by analyzing datasets, selecting suitable algorithms, tuning parameters, performing cross-validated training, and emitting performance metrics plus a saved model artifact.

Astropy Astronomy Toolkit

K-Dense-AI/claude-scientific-skills

Astropy is a Python library for astronomical research that handles unit-aware quantities, celestial coordinates, FITS files, cosmological models, precise time systems, and tabular data, letting you transform, convert, and analyze observational or theoretical datasets.

Data Commons Client

datacommons-client

K-Dense-AI/claude-scientific-skills

Provides a Python client for querying the Data Commons knowledge graph so teams can resolve entities, fetch statistical observations, and explore public demographic, economic, and health datasets with optional Pandas support.

NCBI Gene Explorer

K-Dense-AI/claude-scientific-skills

Access NCBI Gene data via E-utilities or Datasets API to look up genes by symbol or ID, retrieve RefSeqs, GO terms, chromosomal locations, phenotypes, and run batch workflows for annotation pipelines.

Genomic Interval Toolkit

K-Dense-AI/claude-scientific-skills

High-performance Rust toolkit with Python bindings for genomic interval analysis, covering overlap detection, coverage track generation, ML tokenization, reference sequence handling, fragment processing, and scoring workflows for sequencing datasets.

Histolab WSI Tile Processing

K-Dense-AI/claude-scientific-skills

Histolab streamlines whole-slide microscopy by automating tissue detection, tile extraction, and stain normalization for H&E scans, making it ideal for lightweight dataset prep and quick tile-based analysis.

Cancer Imaging Data Access

imaging-data-commons

K-Dense-AI/claude-scientific-skills

Query and download the NCI Imaging Data Commons public cancer imaging datasets via idc-index, filter by metadata, fetch DICOM files, visualize series, and respect licensing details for AI training or research.

LaminDB Biological Data Platform

K-Dense-AI/claude-scientific-skills

LaminDB is a Python-driven open-source framework for managing biological datasets, ensuring traceable, reproducible, FAIR data through lineage tracking, schema validation, ontology annotation, workflow integration, and lakehouse-style querying.

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