codeburn-rs: CodeBurn but 600x faster in Rust

The landscape of AI-assisted coding is rapidly expanding, but with increased usage comes a measurable cost: API tokens. `codeburn-rs` addresses this transparency gap by providing a dedicated tool to monitor and visualize AI coding token consumption. It’s a necessary utility for teams moving from experimental AI use to mission-critical development workflows, offering critical cost awareness that simply isn't visible in standard IDE/platform reporting. What sets `codeburn-rs` apart is its engineering choice. By rewriting the functionality in Rust, the developers solved the performance bottlenecks that plagued earlier iterations of the tool. The provided benchmarks are telling: caching improved output from 6.0ms down to a mere 10.9ms for cached sources, and cold-run usage showed a speedup factor of approximately 101x over the JavaScript version. For any utility that processes potentially large volumes of token data or runs frequently in a CI/CD pipeline, this performance difference is not merely an improvement—it's a necessity for professional adoption. Functionally, the tool is robust. It supports multiple major AI providers, including Claude, Codex, OpenAI, Pi, and Copilot. The command-line interface is well-designed, offering specific subcommands like `cburn today`, `cburn month`, and `cburn report`. The ability to filter reports by provider (e.g., `cburn report --provider claude`) or specify arbitrary date periods adds immense value, turning raw usage data into actionable financial and technical insights. For data analysts or team leads, the `cburn export --format csv` feature is invaluable, allowing the detailed consumption data to be plugged directly into BI tools or custom dashboards. Furthermore, the commitment to a native binary distribution via Homebrew or direct `cargo install` makes integration into developer tooling straightforward. It moves token usage tracking from a simple dashboard view into a reliable, CLI-driven component of the DevOps stack.