Skill UI

A comprehensive guide for developing and managing applications using Amazon Aurora DSQL, a serverless, PostgreSQL-compatible distributed SQL database. This skill covers core capabilities including direct query execution, robust schema management, safe data migration from MySQL, multi-tenant architectural patterns, IAM-based authentication, and detailed query plan explainability for performance tuning. Essential for developers handling complex database evolution.

Builds a robust, automated workflow to export critical sales data—including forecasts, quota details, adjustments, and CRM totals—from Clari CRM to a designated data warehouse. The pipeline supports multiple targets like Snowflake, BigQuery, and PostgreSQL, ensuring that real-time revenue intelligence is available for advanced analytics and business reporting.

A comprehensive guide to setting up and securing API access for Clari. Learn how to generate API tokens, configure environment variables, and test connectivity to export critical revenue intelligence and forecast data to data warehouses like Snowflake or BigQuery. Includes steps for both standard Clari API and Copilot API integration.

Automate the execution of integration tests against a live ClickHouse database instance within a Continuous Integration (CI) pipeline using Docker containers. This setup eliminates the need for mocks, ensuring thorough schema validation and query reliability in environments mirroring production deployments. Ideal for robust CI/CD setup and schema enforcement.

This comprehensive guide provides advanced techniques to diagnose and significantly boost ClickHouse query performance. It covers analyzing slow queries using system tables, optimizing ORDER BY keys, implementing data skipping indexes (Bloom, Set, MinMax), utilizing projections for pre-aggregation, and fine-tuning server settings and materialized views. Essential for high-volume OLAP environments.

Provides a comprehensive, production-ready reference architecture for building advanced analytics platforms powered by ClickHouse. It details everything from project layout (TypeScript/Node.js structure) and data ingestion pipelines (Kafka, Webhooks) to the optimal 3-layer schema design (Raw, Hourly, Daily) and multi-tenancy patterns, ensuring scalable and efficient OLAP query performance.

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.

This guide provides a comprehensive framework for investigating production issues on the Nexu platform using the Datadog Logs API. It details how to query crash events, analyze OpenClaw stderr output, check gateway startup status, and review API request logs (including 5xx errors). It includes best practices for authentication, filtering by pod/time, and parsing raw JSON logs using Python for actionable insights.

This skill provides expert guidance on building and maintaining applications using Amazon Aurora DSQL, a serverless, PostgreSQL-compatible distributed SQL database. It covers critical areas including schema management, multi-tenant architecture, IAM authentication, and safe data migrations (e.g., MySQL to DSQL). Users can execute direct queries, analyze performance bottlenecks using query plan explainability, and adhere to industry best practices for robust, scalable database design.

This skill provides comprehensive guidance for building and managing applications using Amazon Aurora DSQL, a serverless, distributed, PostgreSQL-compatible SQL database. Topics cover schema management, multi-tenant isolation, IAM authentication, complex DDL migrations (column, constraint), MySQL data type mapping, and advanced query performance tuning using plan explainability tools, ensuring robust and scalable data architecture.

A comprehensive tool for managing the entire lifecycle of Feishu Bitable (multi-dimensional table) databases. It supports creating, querying, updating, and deleting records, and managing table fields and views. Ideal for automating complex data workflows, batch data imports, and advanced structured data queries within the Feishu ecosystem.

This SDK provides production-ready patterns for integrating with Fondo's tax and accounting data. It includes a Singleton Client for authenticated REST calls, robust error wrappers (handling retries and authentication), a Query Builder for flexible API requests, and structured types for parsing transactions, accounts, and reports. It is designed for building reliable internal financial tools.