Skill UI

DeepXiv provides a structured and progressive method for accessing open-access academic literature. Instead of forcing the download of entire papers, it allows users to search by topic or ID and progressively read content—from brief overviews and metadata maps to specific sections. This is ideal for researchers who need layered paper access, trend analysis, or quick, targeted knowledge retrieval without overwhelming context.

Utilize the idc-index Python package to access and query massive public datasets from the NCI Imaging Data Commons (IDC). This skill allows users to search, download, and visualize large-scale radiology (CT, MR, PET) and pathology (slide) images. It is essential for AI model training, medical research, and complex medical data analysis.

This skill integrates ten major academic databases (including PubMed, arXiv, OpenAlex, and Semantic Scholar) via REST APIs. It enables comprehensive searches for scholarly articles, preprints, citations, and full-text access across various fields. Use this when searching for research papers on a topic, looking up specific DOIs/PMIDs, or needing global literature metadata.

This guide identifies and provides solutions for common anti-patterns and mistakes when working with Snowflake. It covers best practices in SQL writing, warehouse resource management, data loading strategies (e.g., using MERGE), and access control setup. It is essential for auditing existing deployments, onboarding new users, or performing code reviews to ensure cost efficiency and data integrity.

This comprehensive checklist guides the deployment of Snowflake data pipelines and integrations into a production environment. It covers critical areas such as authentication best practices, warehouse configuration, data pipeline readiness, access control, monitoring setup, and disaster recovery planning. Use it when preparing for a go-live or validating the stability of your production Snowflake setup.

Provides a structured workflow for systematically accessing and analyzing official intellectual property data from the USPTO. This skill covers patent search (PatentSearch API), trademark status checks (TSDR), ownership transfer tracking, and building reproducible IP landscape logs. It is designed for data collection and record verification, emphasizing the use of official APIs and rigorous logging practices. (Warning: Not for legal advice.)

Use the HasData CLI to access real-time, structured web data from major platforms. This tool provides dedicated subcommands for various APIs (including Google SERP, Amazon, Zillow, Booking, etc.), enabling users to automate data collection, scrape specific URLs, and retrieve structured information like local business listings, product pricing, and real estate data directly from the command line.

A powerful command-line utility that transforms virtually any website into a structured CLI command. By utilizing OpenClaw's browser, it allows users to scrape and extract structured data (such as JSON) from over 36 platforms—including social media, finance, and developer communities—directly from the terminal. This tool eliminates the need for complex scraping code or browser extensions, making web data accessible via simple one-liners.

This utility serves as a stub experiment generator, primarily for demonstration purposes within meta-paper writing workflows. Given a specific topic phrase, it deterministically produces a consistent CSV file containing simulated experimental results. This function allows users to prototype and test complex paper structures and formats without needing access to real scientific data.

Comprehensive guidelines covering best practices for Power BI report development. This includes establishing a consistent design identity, applying visual hierarchy rules (like the 3-30-300 rule), managing color discipline, ensuring accessibility, and structuring pages based on their intended question or purpose. It helps transform raw data into professional, actionable, and user-friendly reports.

Run arbitrary PySpark or pure Python code directly on Fabric Spark compute using the Livy API. These sessions are ephemeral, meaning no notebook artifacts are created or persisted, making it ideal for automated ETL processes, programmatic data transformations, or agent-driven compute workflows. Provides full read/write access to lakehouse Delta tables via Spark SQL.

This skill provides deep, cross-border financial analysis and valuation metrics for stocks across multiple markets (e.g., US, HK). Users can access detailed income statements, balance sheets, cash flow data, analyze business segments, compare valuation multiples (PE, PB), run sophisticated DCF models, and perform value screening. It is an essential tool for fundamental research, investment modeling, and corporate analysis.