Skill UI

This comprehensive checklist guides users through critical operational readiness steps for a ClickHouse production deployment. It covers server tuning (config.xml), schema design best practices, robust backup strategies (S3), detailed monitoring setup (Prometheus/Grafana), security hardening, and application integration verification. Use this document before go-live, during major upgrades, or when auditing production systems to ensure maximum stability and performance.

This comprehensive guide details best practices for securing a ClickHouse deployment. It covers essential security measures including role-based access control (RBAC) for granular user permissions, implementing row-level security for multi-tenancy, configuring network IP restrictions, enabling TLS encryption, and setting up detailed audit logging. Use this when hardening a production ClickHouse instance or enforcing strict data governance.

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.

DeepXiv provides a structured and progressive method for accessing open-access academic literature. Instead of forcing the download of entire papers, it allows users to search by topic or ID and progressively read content—from brief overviews and metadata maps to specific sections. This is ideal for researchers who need layered paper access, trend analysis, or quick, targeted knowledge retrieval without overwhelming context.

This skill performs a deep, cross-model audit of experimental results to ensure integrity before claiming findings. It systematically checks for common fraud patterns, such as generating fake ground truths, misleading score normalization, or citing phantom results. Use it when evaluating reported experimental outcomes to ensure methodological rigor and trustworthiness.

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.