Skill UI

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.

This skill guides the setup of CI/CD pipelines for Hex data analytics projects using GitHub Actions. It enables running automated unit tests on pull requests and triggering live project runs on the main branch merge. Use this when establishing automated testing workflows, validating data transformation logic, or integrating Hex outputs into a continuous delivery process.

This guide provides comprehensive solutions for diagnosing and resolving common errors and exceptions encountered while using the Hex data platform. It covers critical areas such as API authentication failures (401, 403), resource not found issues (404), rate limiting, and various run status errors (ERRORED, KILLED). This is essential for debugging failed data requests, optimizing integration workflows, and ensuring stable data analytics pipelines.

This tool collects a comprehensive diagnostic archive for the Hex platform. It gathers crucial evidence, including API connectivity status, project inventory, recent run histories, data connection health, and current rate limit information. Use this bundle when encountering persistent bugs, preparing detailed support tickets, or troubleshooting complex data flow issues.

A comprehensive skill for managing the entire lifecycle of Volcano Jobs within the KubeSphere environment. It supports the scheduling and execution of complex batch workloads, including deep learning tasks using PyTorch and TensorFlow, MPI, and general resource-intensive jobs. Provides detailed API usage and troubleshooting guidance for job scheduling and resource conflicts.

A comprehensive guide for migrating data to, from, and between Notion workspaces. This skill covers complex data pipelines, including rate-limited bulk imports (CSV/JSON), full database exports with pagination, cross-database syncing, and data transformation patterns for integrating content from sources like Confluence and Google Docs. Essential for building robust Notion ETL workflows.

Implement robust data governance and security measures within Palantir Foundry. This skill guides users through PII redaction, applying data markings (e.g., CONFIDENTIAL, RESTRICTED), ensuring GDPR/CCPA compliance, and establishing automated data retention policies. It provides methods for column-level security and auditable deletion workflows for sensitive information.

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 allows for the generation and execution of complex, optimized SQL queries to derive deep business insights. It supports sophisticated data workflows, including multi-table joins, multi-dimensional analysis (e.g., trend analysis, attribution modeling, comparative analysis), and subsequent recommendations for appropriate data visualizations (e.g., line charts, waterfall charts). It goes beyond simple SELECT statements by planning the query structure, handling schema relationships, and ensuring adherence to best practices.

Rowan is a cloud-native molecular modeling and medicinal-chemistry workflow platform with a Python API. It enables pKa prediction, molecular docking, conformer search, and protein-ligand cofolding without local HPC infrastructure. Ideal for batch screening and multi-step chemistry pipelines in drug discovery.

A comprehensive workflow for scraping and extracting structured data from Google search results using the SerpApi. It captures all key components, including organic listings, knowledge graphs, answer boxes, People Also Ask (PAA), local pack results, and related searches. Ideal for SEO monitoring, market research, competitive analysis, or building search-powered features that require deep, structured data insights.

This workflow utilizes the SerpApi to perform advanced, multi-engine searches across platforms including YouTube, Bing, Google News, Google Shopping, and Google Maps. It is essential for data scraping, SEO research, and building comprehensive search features that require aggregating results from diverse sources beyond standard Google search. Use it to collect videos metadata, product pricing, local business details, and news articles efficiently.