Skill UI

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.

Provides a comprehensive checklist for deploying Hex data analytics integrations into production. It covers critical operational best practices, including API key management, rate limit handling, error resilience (circuit breakers, exponential backoff), and robust monitoring strategies. This guide ensures that data pipelines are deployed reliably, minimizing downtime and guaranteeing consistent, high-quality data reporting for go-live scenarios.

This guide provides robust solutions for handling Hex API rate limits, implementing backoff, and ensuring idempotent API calls. It includes a rate limiter class and a retry mechanism with exponential backoff. Use this when building reliable data pipelines, running large-scale batch analytics, or integrating Hex into CI/CD environments where API call throttling is expected.

A comprehensive skill designed to query and download large-scale public cancer imaging data from the NCI Imaging Data Commons (IDC). Utilizing the idc-index package, users can access diverse modalities, including radiology (CT, MR, PET) and pathology datasets. The tool supports complex metadata querying, subset selection by cancer type or anatomical site, and visualization, making it essential for AI model training and scientific medical research. No authentication is required for data access.

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.

Conduct comprehensive, systematic literature reviews across biomedical, scientific, and technical domains. This skill facilitates meta-analyses, scoping reviews, and research syntheses by searching multiple academic databases (e.g., PubMed, arXiv). It generates professionally formatted reports (Markdown/PDF) with verified citations and mandates the inclusion of AI-generated scientific schematics (e.g., PRISMA flow diagrams). Ideal for academic research and thesis writing.

This skill provides comprehensive patterns for extracting and transforming Navan booking and transaction data. It addresses complex data pipeline challenges such as API pagination, date range chunking, and UUID-based deduplication. It supports both direct REST API implementation (via code examples) and configuration for managed connectors like Fivetran and Airbyte. Ideal for populating data warehouses, building robust analytics dashboards, or ensuring data quality from Navan sources.

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.

A comprehensive, structured framework for conducting sophisticated Open Source Intelligence (OSINT) and cryptocurrency forensic investigations. This guide covers operational security (OpSec), target profiling, advanced transaction tracing across multiple blockchain layers (L1/L2), wallet analysis, and identifying linked digital assets. Use this methodology to guide systematic, multi-dimensional intelligence collection campaigns.

This guide provides comprehensive technical instructions for optimizing Palantir Foundry costs. Learn to use incremental transforms to drastically reduce compute rebuilds, right-size Spark profiles based on data volume, and migrate from expensive API polling to efficient, event-driven webhooks, ensuring both cost efficiency and system stability.