claude-token-efficient is a prompt optimization tool that reduces token consumption by constraining Claude's response verbosity through a single instruction file.
The tool addresses the problem that Claude's default behavior includes unnecessary flourishes—opening pleasantries, closing remarks, Unicode characters, question restatement, and unsolicited suggestions—that consume tokens without adding value. The approach is straightforward: a CLAUDE.md file containing formatting and style rules is dropped into a project and automatically applied to every message in that session. The file instructs Claude to respond tersely, avoid decorative language, use ASCII-safe characters, and skip preamble. Users can override the rules on a per-message basis when needed. The tool also offers a quick-start alternative of pasting rules directly into chat for one-off tasks.
Adoption makes sense for automation pipelines and repeated structured tasks where high output volume justifies the persistent input cost of loading the instruction file. Resume bots, agent loops, and code generation workflows benefit most. The tool is not worth using for single short queries, casual one-off interactions, or exploratory work where alternatives and debate are central to the task. The README explicitly cautions that the file itself consumes input tokens on every message, so the net savings only materialize when output volume is high enough to offset that overhead. For guaranteed parseable output at scale, the README recommends using structured outputs built into the API rather than prompt-based formatting rules. The tool has been benchmarked on Claude only; the rules are model-agnostic but untested on local models like llama.cpp or Mistral.
Development appears minimal and focused. The repository consists of a single instruction file with accompanying documentation, reflecting a deliberately simple design philosophy. The README emphasizes keeping the instruction file short to avoid token cost inversion, suggesting the maintainer has thought carefully about the trade-offs inherent in the approach. The project includes honest guidance about when the tool does and does not pay for itself, indicating pragmatic rather than promotional framing.
