Show HN: OpenSlimedit – Cut AI coding token usage by 21-45% with zero config (github.com)

OpenSlimedit, a new OpenCode plugin, promises to reduce token usage in AI coding tasks by 21-45% without requiring any configuration. It achieves this via three primary optimizations: compressing tool descriptions, compacting read outputs, and enabling line-range edit support. During extensive testing across various AI models, including GPT 5.3 Codex and Claude Opus 4.6, OpenSlimedit consistently outperformed previous methods, leading to significant savings in token utilization—up to 45.1% in some cases. This development is particularly noteworthy for the AI/ML community, as token efficiency directly impacts performance and cost-effectiveness when using language models for coding tasks. By reducing the overhead associated with tool descriptions sent in API calls and adopting a more streamlined editing approach, OpenSlimedit not only enhances the practical use of AI for developers but also opens the door for more complex interactions with less resource consumption. The implementation requires minimal setup, making it an attractive option for developers looking to optimize their AI coding workflows without compromising on functionality.