Skill UI

A powerful tool designed to monitor blockchain mempools, analyzing pending transactions, gas price fluctuations, detecting DEX swaps, and identifying potential MEV opportunities. It is essential for advanced crypto traders, MEV researchers, and protocol developers who need to optimize transaction timing and gas costs across multiple EVM chains (Ethereum, Polygon, Arbitrum, etc.).

A powerful tool designed to monitor blockchain mempools, analyzing pending transactions, gas price fluctuations, detecting DEX swaps, and identifying potential MEV opportunities. It is essential for advanced crypto traders, MEV researchers, and protocol developers who need to optimize transaction timing and gas costs across multiple EVM chains (Ethereum, Polygon, Arbitrum, etc.).

Automates change-data-capture pipeline planning by guiding developers through ETL, orchestration, and streaming best practices, then generating validated configs and code when “cdc pipeline creator” is requested.

A comprehensive tool for querying and analyzing deep blockchain data across multiple EVM-compatible networks, including Ethereum, Polygon, Arbitrum, and Optimism. It supports tracking transactions by hash, checking address balances, inspecting blocks, and resolving ERC-20 token holdings. Ideal for crypto analysts, developers, and researchers requiring programmatic, detailed insights into on-chain financial activity and protocol interactions.

This comprehensive workflow guides developers through implementing full-stack product analytics using PostHog. It covers key areas including defining event taxonomies, capturing user actions (client-side), identifying and updating user properties, and performing B2B group analytics. It also demonstrates server-side event tracking using posthog-node, ensuring a complete, accurate, and traceable view of user behavior and product usage across web, mobile, and API sources.

Guides developers through scikit-learn workflows for classical supervised and unsupervised tasks, data preprocessing, evaluation schemes, hyperparameter tuning, and end-to-end pipelines when building interpretable production models.

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.

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 manages the complexities of Clari API version changes, ensuring smooth transitions (e.g., v3 to v4). It guides developers through detecting schema drift, performing data field compatibility checks, and executing necessary database migrations (SQL/Python), ensuring reliable data pipelines after platform updates.

A structured guide for setting up a robust local development environment for Palantir Foundry data pipelines. This workflow enables users to run Python transforms and unit tests using PySpark against sample data, and mock the Foundry API client, ensuring fast, isolated iteration cycles before deploying code to the official Foundry environment. Ideal for data engineers and developers building complex ETL logic.

This skill converts vague business questions or monitoring needs into a complete, structured, and implementation-ready dashboard specification. It guides users to define key metrics (KPIs), chart types, axes, filters, and optimal layout, providing data engineers and BI developers with all necessary details to build the dashboard without ambiguity.

A comprehensive set of programmatic interfaces for RuView's Wi-Fi sensing capabilities, including the CLI binary, REST API, and WebAssembly builds. This toolkit allows developers to integrate sophisticated disaster survivor detection and signal analysis into various environments, such as scripting, web browsers, and edge devices (ESP32-WASM3). Ideal for systems requiring cross-platform, scalable sensing data streams.