AI Skills for Data Engineer

Guides the creation of high-quality MCP servers for LLMs, enabling integration with external APIs using Python or TypeScript.

Automates browser interactions for testing, form filling, and data extraction, enabling efficient web navigation and information retrieval.

Provides patterns for using the Anthropic Claude API in Python and TypeScript, enabling efficient application development.

Covers best practices for designing REST APIs, including resource naming, status codes, and error handling for robust API development.

Provides best practices for backend architecture, API design, and database optimization in Node.js, Express, and Next.js.

Provides best practices for ClickHouse database patterns, query optimization, and analytics for high-performance data engineering.

Provides idiomatic Go patterns and best practices for building robust, efficient, and maintainable applications.

Provides JPA/Hibernate patterns for efficient entity design, query optimization, and transaction management in Spring Boot applications.

Provides best practices for database migrations, covering schema changes, data migration, rollback, and zero-downtime deployments.

Caches expensive file processing results using SHA-256 content hashes, ensuring efficiency and automatic invalidation on content changes.

Enforces modern C++ coding standards based on core guidelines to ensure safe and idiomatic practices in C++ development.

Provides PostgreSQL database patterns for query optimization, schema design, indexing, and security based on Supabase best practices.

Provides a structured template for project guidelines, including architecture, file structure, and deployment workflows.

Guides Clojure and ClojureScript development with REPL-driven workflows and best practices for efficient coding and refactoring.

Automates mutation testing in Clojure, generating tests and draft PRs while integrating with Linear for issue tracking.

Facilitates the addition of Malli schemas to API endpoints in Metabase, ensuring proper validation and error handling.

Facilitates building read models and projections from event streams for optimized query performance in event-sourced systems.

Enables secure, high-performance connectivity between on-premises infrastructure and cloud platforms for hybrid cloud architectures.

Enables comprehensive observability for service meshes with distributed tracing, metrics, and visualization for effective monitoring.

Facilitates seamless database migrations with zero-downtime strategies, ensuring smooth transitions and data integrity.