What problem does it solve? Setting up a new Rust project involves many decisions: binary vs library crate, workspace layout, Cargo.toml manifest fields, edition settings, features, and build profiles. This Skill provides structured templates and best practices so AI agents and developers can scaffold correct, idiomatic Rust projects without memorizing Cargo configuration details. ## Core Features & Use Cases - Project Scaffolding: Guidance for cargo new, cargo init, binary vs library crates, and recommended directory layouts including tests, benches, and examples. - Cargo.toml Templates: Ready-to-use manifest templates covering edition 2024, rust-version, features with optional dependencies, release profile optimization (lto, strip, codegen-units), and clippy lint configuration. - Workspace Management: Multi-crate workspace setup with resolver v2, workspace.package inheritance, and workspace.dependencies for centralized version control. - Use Case: When starting a new Rust CLI tool, ask the AI to generate the project structure and it will produce a complete Cargo.toml with proper profiles, lints, and a modular src layout with config and error modules. ## Quick Start Ask the AI to initialize a new Rust project with a Cargo.toml configured for edition 2024, release optimizations, and clippy lints.