Skill UI

This guide details how to set up and execute large-scale, distributed GPU training jobs on the CoreWeave platform. It covers both single-node multi-GPU setups and multi-node training utilizing PyTorch DDP and Kubernetes resources (A100/H100). This workflow is ideal for fine-tuning large language models (LLMs) or running complex deep learning models that require high-performance, shared-storage compute clusters.

This guide demonstrates how to deploy GPU workloads on the CoreWeave platform using Kubernetes (kubectl). It covers deploying vLLM inference services for large language model (LLM) testing and running batch CUDA jobs for benchmarking. This is ideal for users running their first GPU workloads, testing inference pipelines, or verifying cluster access on bare-metal GPU nodes (A100, H100).

This expert acts as a dedicated data analysis partner for Product Managers. It helps users explore data, write complex queries (e.g., SQL, BigQuery), analyze key metrics, and create structured dashboards. Use this tool when you need to derive actionable insights from complex datasets, compare user cohorts, or understand product performance trends to inform critical business decisions.

A comprehensive tool for creating high-quality training datasets for custom object detection and segmentation models. It supports multiple advanced annotation methods including BBox drawing, SAM2 pixel-perfect segmentation, and DINOv3 visual grounding. Features include AI auto-detection, object tracking, and standardized COCO format export, streamlining the entire data pipeline from capture to training.

This workflow automates the extraction of key insights from meeting recordings using Fathom transcripts and summaries. It builds a robust pipeline to identify action items, sync tasks to project management tools, and analyze overall meeting patterns, streamlining post-meeting follow-up and record-keeping.

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.

Comprehensive toolkit for managing sensitive Flexport supply chain data, including shipment records, customs declarations, and financial invoices. This skill enforces strict data governance, handling PII redaction, ensuring GDPR/CCPA compliance, managing mandated data retention periods (e.g., 5-7 years), and blocking restricted export items (ITAR) to maintain global trade compliance standards.

Implements a robust data pipeline for handling large documents with the Grammarly API. This utility manages text chunking to comply with API character limits (max 100k), processes text in manageable segments, and aggregates multiple scoring metrics (like correctness, clarity, and tone) into a single, comprehensive report. Ideal for large-scale content analysis and data ingestion.

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.