Skill UI

A comprehensive guide to modern backend development patterns for scalable server-side applications using Node.js, Express, and Next.js. Covers API design (RESTful), data access patterns (Repository, Service Layer), database optimization (N+1 prevention, Transactions), and advanced caching strategies (Redis, Cache-Aside). Essential for building robust, high-performance APIs.

A comprehensive reference guide for structuring development projects within the Cursor IDE. It details best practices for directory layout, defining layered rules (covering global conventions, security constraints, and technology-specific patterns like API routes and database access), and optimizing indexing strategies. This ensures maximum AI effectiveness, improves code maintainability, and streamlines the entire development workflow.

This skill details best practices for handling and structuring Evernote data. It covers designing local database schemas (SQL), advanced ENML content processing (to Markdown/HTML), managing attachments, and implementing reliable incremental synchronization using Update Sequence Numbers (USN). Ideal for developers building robust applications requiring deep, local data access and integrity checks for Evernote content.

Comprehensive guide to managing data securely in Replit applications. This skill covers three core storage systems: PostgreSQL for structured data and complex queries; Replit KV Database for caching and session management; and Object Storage for file uploads and blobs. Learn best practices including parameterized queries, TTL implementation, and secure data access patterns.

This guide provides production-ready coding patterns for interacting with various built-in Replit services. It covers best practices for setting up singleton clients, implementing robust error handling, and creating type-safe wrappers for Key-Value Database, Object Storage, PostgreSQL, and Auth middleware. Ideal for developers building complex Replit integrations or establishing standardized data access layers.

A comprehensive guide to implementing secure secrets management practices for Continuous Integration/Continuous Deployment (CI/CD) pipelines. It covers using industry-leading tools like HashiCorp Vault, AWS Secrets Manager, Azure Key Vault, and GCP Secret Manager to securely store, retrieve, and automatically rotate credentials (API keys, database passwords, TLS certificates) without hardcoding them into source code. Includes best practices for least-privilege access and audit logging.

Biopython provides Python APIs for sequence manipulation, database access, BLAST automation, structural bioinformatics, and phylogenetics, making it ideal for scripting custom pipelines and batch processing in computational molecular biology workflows.

Leverages PubChem’s PUG-REST API or PubChemPy to search 110M+ compounds by name, CID, or structure, fetch properties, perform similarity/substructure lookups, and access bioactivity or format conversions for cheminformatics workflows.

Provides access to USPTO PatentSearch, PEDS, TSDR, and related APIs for patent and trademark searches, examination history, assignments, citations, and litigation data, with helper scripts for Python-based IP research and portfolio insights.

A comprehensive guide to building robust database layers in Kotlin using the Exposed ORM framework. It covers advanced patterns including DSL queries, DAO entity management, transaction handling, connection pooling with HikariCP, schema migration via Flyway, and implementing the Repository pattern for clean, production-grade data access.

A comprehensive, type-safe in-memory caching library for Go, designed for advanced system architecture. It supports nine sophisticated eviction algorithms (like W-TinyLFU, LRU, LFU, ARC) to optimize cache hit rates based on specific access patterns. Key features include TTL management, loader chains for read-through caching (with singleflight deduplication), sharding, and Prometheus metrics. Ideal for high-frequency services needing to reduce database load and latency.

Automates the generation of robust, DB-agnostic integration test cases for data access layers (DAL) during major database migrations, specifically from Oracle to PostgreSQL. These tests validate behavioral consistency across both source and target database systems, ensuring that core business logic remains intact after the migration process. Essential for maintaining data integrity and application stability.