Skill UI

This skill provides comprehensive management for annotation schemas (configs) and human review workflows (queues) within the Arize platform. It supports defining categorical, continuous, and freeform label types. Users can programmatically apply these annotations to project spans and datasets using the Python SDK, facilitating structured human feedback loops and improving model monitoring.

This skill guides users on automating fundraising workflow analysis using local data methods. Since Finta lacks a public API, it teaches how to export pipeline data (CSV) and use Python (Pandas) scripts to calculate key funnel metrics, conversion rates, and generate detailed weekly reports for investor tracking and reporting.

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.

A comprehensive project management guide for planning submissions to KDD, accounting for its unique structure of two annual submission cycles. It covers milestone tracking, cycle-choice decision matrices, managing the Resubmit loop, and planning evidence lead times from abstract to camera-ready status. Essential for complex, multi-stage data science research.

Guides investigation of broad process mining questions, observed patterns, or competing explanations across analytical perspectives, using an evidence loop to test claims and route to specialists.

Query Microsoft Fabric and Power BI semantic models with DAX to build trustworthy dashboards: reuse governed measures, design KPIs with target and trend, wire crossfiltering, and test queries with an execute-inspect-fix loop.