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claude-token-efficient is a lightweight configuration-based optimization project designed to reduce the verbosity and token usage of Claude-powered coding workflows through a structured instruction file. Instead of modifying model architecture or APIs, it uses a drop-in CLAUDE.md file that constrains how the model responds, enforcing concise output and eliminating unnecessary phrasing patterns. The approach focuses on removing redundant explanations, overly polite language, and repeated context, which are common contributors to excessive token consumption in AI-generated responses. It is particularly useful in high-volume or agent-based workflows where output tokens accumulate quickly and significantly impact cost and latency. The system works best in iterative or automation-heavy environments where consistent formatting and brevity are more valuable than exploratory reasoning.
Features
- Drop-in CLAUDE.md configuration for immediate use
- Reduction of verbose and redundant model outputs
- Enforcement of concise and structured responses
- Optimization of token usage in high-volume workflows
- Compatibility with existing Claude-based environments
- Focus on cost and latency efficiency improvements
Project Samples
