Skill UI

Generates Python code and workflows for collaborative, content-based, or hybrid recommendation models, handling data prep, training, evaluation, and scalability so Claude can deliver tailored suggestions across domains.

A comprehensive pipeline for processing, validating, and optimizing scraped web content from Firecrawl. This tool handles markdown cleaning, structured data extraction using Zod validation, content deduplication, and chunking tailored for Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) systems. It ensures crawled data is standardized, clean, and ready for downstream consumption or knowledge base indexing.

Master the implementation of Firecrawl webhooks for robust, real-time handling of asynchronous crawling and batch scraping jobs. Instead of inefficiently polling the crawl status, configure webhook endpoints to receive instant POST events (e.g., `crawl.page`, `crawl.completed`). This guide covers event types, signature verification using HMAC-SHA256, and processing streamed data for building advanced data pipelines.

This skill manages the complete lifecycle of Fireflies.ai meeting transcripts. It allows users to fetch raw data, export in various formats (JSON, CSV, SRT), sanitize sensitive personal information (PII Redaction), and enforce data retention policies to ensure compliance with regulations like GDPR and CCPA. Ideal for data governance and compliance workflows.

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.

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

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.

A comprehensive skill for managing the entire lifecycle of datasets on the Hugging Face Hub. It allows users to initialize, configure, and stream updates for datasets of various types (Chat, Text Classification, Tabular). Crucially, it extends data handling capabilities by enabling powerful SQL-based querying and transformation directly on Hub datasets using the DuckDB engine, facilitating advanced data exploration and pipeline creation.

Automates the generation of high-quality, publication-ready figures and comparison tables from raw experimental data (JSON, CSV). This skill is essential for academic writing workflows, handling various plot types including line graphs, bar charts, scatter plots, and heatmaps, ensuring consistency with professional style guides like LaTeX and specific DPI requirements.

A comprehensive Python library for professional astronomy and astrophysics data analysis. It provides essential tools for handling celestial coordinates, physical units, FITS file I/O, time systems, and cosmological calculations, making it vital for scientific research in space science.

Datamol is a high-level, Pythonic abstraction layer built over RDKit, designed for computational chemistry and drug discovery. It simplifies complex molecular operations, offering sensible defaults for tasks like SMILES standardization, descriptor calculation, fingerprint generation (ECFP4), 3D conformer analysis, and molecular clustering. It supports efficient parallel processing and cloud storage I/O, making it ideal for handling large-scale chemical datasets.

A comprehensive guide for advanced geospatial data processing using GeoPandas. This skill targets professional workflows involving planar vector data, emphasizing rigorous data provenance, coordinate reference system (CRS) management, and complex spatial operations. It details necessary safety contracts, correctness gates, and best practices for handling sensitive geographic information in reproducible Python environments.