Skill UI

This skill manages the complex process of upgrading AppFolio API integrations. It automatically detects current and latest API versions, handling breaking changes such as renamed fields, altered pagination models, and deprecated endpoints. The tool provides schema migration transforms and implements a robust rollback strategy, ensuring stable data synchronization during major platform updates.

A comprehensive diagnostic utility designed to collect all necessary evidence when troubleshooting Attio API connectivity issues or preparing a support ticket. It checks API authentication, object schema definitions, rate limit status, and general endpoint health using shell scripting and cURL.

A comprehensive skill guide for Amazon Aurora DSQL, a serverless, PostgreSQL-compatible distributed SQL database. This resource covers the entire database lifecycle, including schema management, multi-tenant architecture, advanced DDL migrations (e.g., column operations, constraint changes), and MySQL schema migration. It provides best practices for security (IAM auth), performance tuning (query plan explainability), and safe application development.

This skill provides comprehensive guidance for working with Amazon Aurora DSQL, a serverless, PostgreSQL-compatible distributed SQL database. It covers direct query execution, robust schema management, multi-tenant isolation, IAM authentication, and detailed procedures for handling complex migrations (DDL/MySQL) and optimizing query performance using explain plans. Use it for building resilient, scalable applications.

This advanced guide covers core Anthropic workflow patterns, specifically focusing on tool use (function calling) and building complex, agentic loops. It provides detailed instructions on defining tools using JSON Schema, executing tool calls, and managing the iterative process required for building sophisticated, AI-powered agents using the Anthropic API.

This skill manages the complexities of Clari API version changes, ensuring smooth transitions (e.g., v3 to v4). It guides developers through detecting schema drift, performing data field compatibility checks, and executing necessary database migrations (SQL/Python), ensuring reliable data pipelines after platform updates.

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.

A comprehensive guide to designing high-performance schemas in ClickHouse. Learn how to select the optimal MergeTree engine (e.g., ReplacingMergeTree, AggregatingMergeTree), structure the ORDER BY key for maximum query efficiency, and implement effective partitioning strategies for large-scale analytical workloads and ETL processes.

Provides comprehensive methods for executing ClickHouse schema migrations, including column changes, engine migrations, and complex modifications like changing ORDER BY. It teaches best practices for zero-downtime schema updates and implements a versioned migration runner pattern for robust data evolution.

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.

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 skill provides comprehensive tools and guides for interacting with Amazon Aurora DSQL, a serverless, PostgreSQL-compatible distributed SQL database. Users can manage schemas, execute complex queries, handle database migrations (including MySQL to DSQL), implement multi-tenant patterns, and diagnose query performance using detailed explain plans. Ideal for backend development and database evolution.