📄 中文摘要
在 OpenClaw 环境中，团队通常通过缩短提示、简化输出或使用更便宜的模型来降低大语言模型（LLM）的成本。然而，最大的浪费往往源于低效的运行时行为，如故障的回退链、提供者/认证不匹配、过时的会话上下文以及不一致的代理配置。这些问题会导致更多的重试、更高的令牌使用、更大的延迟和日志中的噪声。因此，优化运行时行为应优先于优化提示。
停止在 OpenClaw 中浪费令牌
出处: Stop met tokens verspillen in OpenClaw
发布: 2026年3月15日
📄 English Summary
Stop met tokens verspillen in OpenClaw
In OpenClaw environments, teams often attempt to reduce costs associated with large language models (LLMs) by shortening prompts, condensing outputs, or using cheaper models. However, the most significant waste typically arises from inefficient runtime behavior, such as broken fallback chains, provider/auth mismatches, outdated session contexts, and inconsistent agent configurations. These issues can lead to increased retries, higher token usage, greater latency, and noise in logs. Therefore, optimizing runtime behavior should take precedence over optimizing prompts.