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A comprehensive guide derived from C++ Core Guidelines, enforcing modern, safe, and idiomatic practices for C++17, C++20, and C++23. It emphasizes crucial principles like RAII, type safety, immutability, and proper resource ownership using smart pointers. Use this when writing new features, reviewing existing code, or making architectural decisions to ensure code quality and consistency.

A comprehensive guide to production-ready patterns for the Databricks Python SDK. This skill covers essential best practices including singleton client initialization, structured error handling with typed exceptions, context-managed cluster lifecycle control (ensuring cleanup), and implementing type-safe job definitions. It is essential for building robust, maintainable, and idiomatic integrations with the Databricks platform.

This skill generates robust, type-safe client Software Development Kits (SDKs) for multiple languages (including Python, TypeScript, Go, and Java) directly from OpenAPI 3.0+ specifications. It automatically handles complex API patterns such as authentication (Bearer, OAuth2), automatic retries with exponential backoff, and sophisticated pagination helpers. Use this when you need to create standardized, idiomatic client libraries to consume a defined API contract across diverse development stacks.

Curated guidelines covering idiomatic Go error handling, interface design, concurrency patterns, context propagation, testing, and module management for reliable team codebases.

This skill simulates a senior Go developer, specializing in writing high-performance, production-grade Go applications. It covers advanced topics like concurrent programming using goroutines and channels, designing robust microservices with gRPC/REST, and optimizing code using pprof and benchmarks. It enforces idiomatic Go patterns, context propagation, and strict testing practices (table-driven, fuzzing, race detection).

A specialized AI assistant acting as an expert Haskell engineer. This skill focuses on advanced type systems (GADTs, type families), pure functional architecture, concurrency (STM, async), and high-assurance software design. Use it for building robust, idiomatic, and maintainable Haskell code.

A concise collection of idiomatic Python best practices—from readability and explicit configuration to type hints, error handling, and context managers—aimed at building robust, maintainable applications.

This skill acts as an expert guide for developing clean, idiomatic, and highly performant Ruby code. It specializes in the entire Rails ecosystem, covering metaprogramming, ActiveRecord patterns, gem development, and comprehensive testing using RSpec/Minitest. Use it to ensure best practices, optimal code structure, and maintainable architecture in Ruby projects.

Expert skill for writing, reviewing, and debugging idiomatic Rust code, focusing on memory safety and zero-cost abstractions. Specializes in advanced concepts like ownership patterns, explicit lifetime management, trait-based API design, and building concurrent async applications using Tokio. Use this when developing high-performance, reliable, systems-level software in Rust.

This skill acts as an expert architect for scaffolding production-ready Rust applications. It generates complete, idiomatic, and robust project structures suitable for binary CLI tools, reusable libraries, and complex multi-crate workspaces (monorepos). It ensures adherence to Rust best practices, including proper module organization, advanced Cargo dependency management, and comprehensive testing setup.

Guides Odoo developers through search, browse, create, write, domain filters, relational and computed field patterns, and performance-safe bulk operations while responding to @odoo-orm-expert prompts for idiomatic code and optimizations.

A comprehensive guide to building robust, maintainable, and idiomatic Perl applications using modern features (Perl 5.36+). This resource covers best practices for object-oriented programming (Moo/Moose), advanced error handling (Try::Tiny), context sensitivity, complex regex usage, and efficient module design.