Skill UI

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.

A comprehensive skill for ingesting, analyzing, and manipulating multi-modal video and audio content. Supports real-time desktop capture, live stream monitoring (RTSP), and file uploads (URL/local). Capabilities include advanced indexing (visual, semantic, temporal), precise moment searching, professional timeline editing (subtitles, overlays, dubbing), transcoding, and generating actionable alerts. Ideal for content creators, monitoring systems, and complex media workflows.

This sophisticated workflow guides users from a broad research concept or initial topic to a fully validated, actionable, and pilot-tested research idea. It orchestrates a multi-stage pipeline, including literature surveys, novelty checks, detailed idea generation, critical review, and the creation of a refined experimental plan, ensuring the output is a robust proposal ready for implementation.

This skill orchestrates the entire academic research lifecycle, transforming a broad research direction into a polished, publishable paper. It sequentially manages idea discovery, literature review, experimental implementation, cross-model review, and final manuscript writing, supporting autonomous or manually guided advanced research workflows.

Provides direct REST API access to UniProt, the premier resource for protein sequence and functional information. This skill enables users to search proteins by name, gene, or accession number, retrieve sequences in FASTA format, perform cross-database ID mapping (e.g., Ensembl, RefSeq), and analyze functional annotations (GO terms) for building comprehensive bioinformatics pipelines.

A comprehensive solution for systematically auditing dataset health. It profiles data distributions, detects missing values (MCAR/MAR/MNAR), identifies outliers using multiple methods (IQR, Z-score), and calculates a Data Quality Score (DQS). It provides actionable remediation plans and supports monitoring setup for live pipelines.

A powerful toolset for automating core PostHog product analytics tasks via Rube MCP. It enables developers and analysts to capture user events, list and filter event data, manage feature flags (creation, retrieval, listing), and inspect user profiles. Ideal for integrating advanced product tracking and A/B testing workflows directly into development pipelines.

Reviews Python + BigQuery pipelines to flag runaway costs, missing dry-run safeguards, unsafe backfills, write idempotency issues, and monitoring gaps, returning a structured report with exact function/line references for minimal fixes.

Structured pipeline for credit risk pre-loan modeling that loads and formats raw data, filters abnormal periods, trims high-missing/low-IV/high-PSI/high-correlation features, denoises via Null Importance, and exports an Excel cleaning report for review.

Surfaces Monte Carlo data observability insights—health, lineage, alerts, and monitors-as-code—before developers edit dbt models or SQL pipelines, ensuring risk-aware code changes.

This skill automatically generates an interactive SQL Notebook designed to validate changes in dbt models or snapshots. It processes changes identified from a GitHub PR or local repository, generating comparison queries that compare 'before' (production) and 'after' (development) data states. It is essential for embedding data observability and quality checks into CI/CD pipelines.

Biopython is a comprehensive Python library designed for molecular biology and bioinformatics. It provides powerful tools for sequence manipulation (DNA, RNA, Protein), parsing standard biological file formats (FASTA, GenBank, PDB), accessing external databases like NCBI (PubMed, GenBank) via Entrez, and performing complex analyses such as sequence alignment, phylogenetic tree construction, and structural bioinformatics. Ideal for building robust, automated bioinformatics pipelines.