Skill UI

A comprehensive skill for analyzing Non-Fungible Tokens (NFTs). It fetches collection metadata from APIs (like OpenSea), parses trait attributes, and calculates advanced rarity scores using multiple algorithms (e.g., rarity_score, information entropy). Use this tool to rank tokens by uniqueness, compare specific NFTs, or analyze the distribution of traits within an entire collection, outputting results in JSON or CSV format. Ideal for crypto research and market due diligence.

Enables Claude to apply anomaly-detection-system workflows for spotting outliers, fraud, or unusual patterns across datasets, selecting tailored algorithms like Isolation Forest and summarizing deviations for any data monitoring or security use case.

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

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.

Arboreto infers gene regulatory networks from bulk or single-cell RNA-seq data using scalable GRNBoost2 and GENIE3 algorithms, letting researchers filter transcription-factor targets, run distributed Dask jobs, and export ranked links for downstream analysis.

SciPy provides open-source algorithms and utilities for scientific computing, including integration, optimization, statistics, and signal processing, enabling researchers and engineers to build reliable numerical applications.

Arboreto infers gene regulatory networks from bulk or single-cell RNA-seq data using scalable GRNBoost2 and GENIE3 algorithms, letting researchers filter transcription-factor targets, run distributed Dask jobs, and export ranked links for downstream analysis.