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Comprehensive Rust testing patterns for writing reliable, maintainable tests following TDD methodology.

Comprehensive pytest testing strategies with TDD, fixtures, mocking, and coverage best practices. \n \n Covers TDD methodology (red-green-refactor cycle), parametrization, fixtures with multiple scopes, and mocking patterns for unit and integration testing \n Includes pytest fundamentals: assertions, markers for test selection, exception testing, and async test support with pytest-asyncio \n Provides practical patterns for testing APIs, databases, file operations, and class methods with real cod

Persona: You are a Go engineer who treats caching as a system design decision. You choose eviction algorithms based on measured access patterns, size caches from working-set data, and always plan for expiration, loader failures, and monitoring.

Standards and best practices for Python development. Follow these guidelines when writing or modifying Python code.

Operation-aware node configuration with progressive discovery and property dependency management. \n \n Start with get_node({detail: \"standard\"}) for 95% of configuration needs; escalate to full detail or search_properties mode only when standard doesn't provide required information \n Resource and operation determine which fields are required; use validation iteratively to discover conditional dependencies controlled by displayOptions rules \n Common patterns include resource/operation nodes

Generate a Spring Boot 3.4.5 project skeleton with PostgreSQL, Redis, MongoDB, and Docker Compose. \n \n Scaffolds a Maven-based Spring Boot project with Java 21, including Lombok, Spring Data JPA, Spring Web, caching, and validation dependencies \n Pre-configures application.properties with connection details for PostgreSQL, Redis, and MongoDB, plus SpringDoc OpenAPI for API documentation \n Generates a docker-compose.yaml file with Redis 6, PostgreSQL 17, and MongoDB 8 services, each with pers

Web search and content scraping via DuckDuckGo with configurable result limits. \n \n Provides two core commands: search for querying the web with customizable result counts, and fetch_content for scraping full page content from URLs \n Integrates with the DuckDuckGo MCP Server for real-time search results and webpage extraction \n Useful for agents that need to gather current information, verify facts, or extract text from live web pages \n

Generate production-ready Python code for Dataverse SDK with error handling and best practices. \n \n Implements comprehensive error handling using DataverseError hierarchy with retry logic and exponential backoff for transient failures \n Enforces singleton client pattern for connection management and includes structured logging for audit trails and debugging \n Applies OData optimization techniques: server-side filtering, column selection, and pagination to reduce data transfer \n Provides typ

JavaScript client for connecting to Rivet Actors with stateless or stateful connections. \n \n Supports browser, Node.js, and Bun environments with automatic endpoint detection via environment variables or explicit configuration \n Offers two interaction modes: stateless action calls for independent requests and stateful connections with real-time event subscriptions \n Includes low-level HTTP and WebSocket access for actors implementing onRequest or onWebSocket handlers \n Provides compound arr

Pytest-based testing strategies for Temporal workflows with time-skipping, mocking, and replay validation. \n \n Covers unit testing (WorkflowEnvironment with time-skipping), integration testing (mocked activities), and replay testing for determinism validation \n Time-skipping enables month-long workflows to execute in seconds; ActivityEnvironment isolates activity logic for fast feedback \n Includes progressive disclosure resources for unit testing, integration testing, replay testing, and loc