Skill UI

This skill replaces detected Protected Health Information (PHI) in clinical notes with realistic, type-matched synthetic surrogates. Unlike simple redaction, surrogates maintain the natural readability and structure of the text, ensuring the data remains parseable for downstream NLP tasks, QA, or human review. It supports consistent, reproducible fake identities and allows custom identifier generation for proprietary formats.

A comprehensive toolkit for the entire lifecycle of spreadsheet data, including creation, sophisticated editing, deep analysis, and visual reporting. It supports various formats (.xlsx, .csv) and is designed for professional tasks such as building complex financial models, generating reports with precise formatting, and analyzing raw tabular data while meticulously preserving formulas and structure.

This skill provides specialized guidance and structured patterns for conducting scientific research and analysis tasks. It helps users formulate hypotheses, design experiments, analyze data, and interpret results within a scientific context. Use this when the task involves rigorous scientific methodology, literature review, or technical analysis requiring expert-level reasoning. It is not a substitute for professional validation or safety checks.

Explore and extract Hugging Face datasets using the Dataset Viewer API. Perform read-only operations like validating datasets, listing splits, previewing rows, paginating, searching text, filtering, retrieving parquet links, and getting statistics. Ideal for data exploration and retrieval tasks.

A powerful tool for deterministic and reproducible retrieval of evidence from specialized academic and policy corpora. It supports searching arXiv (preprints), PubMed/PMC (biomedical literature), and US policy documents. Users can check corpus freshness, retrieve stable metadata, and fetch full-document Markdown for high-reliability research tasks.

A comprehensive automation toolkit for Mixpanel product analytics, accessible via Rube MCP. Automate key data tasks including event aggregation, detailed segmentation, conversion funnel analysis, user profile management, cohort tracking, and running custom JQL queries. Ideal for data analysts and product managers needing to deeply analyze user behavior patterns.

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.

Build financial models, backtest trading strategies, and analyze market data. Implements risk metrics, portfolio optimization, and statistical arbitrage. Uses Python libraries like pandas and numpy for algorithmic trading and financial modeling tasks.

This skill helps plan and review read-only data warehouse analysis with explicit scope, privacy, and validation checks. It turns business questions into reproducible analysis plans without assuming specific schemas. It identifies needed data, reviews proposed queries for risks like grain or privacy, and ensures results are communicated accurately. Suitable for authorized data warehouse usage, query review, and analysis documentation while avoiding administrative tasks.