When transitioning between tasks, accumulated context from previous interactions can significantly inflate token usage. Claude re-reads the entire conversation history with every new message. To prevent this, always use the" /clear "command in Claude Code when starting a new task or changing topics. This action effectively resets the session, ensuring that Claude only processes the relevant information for your current objective, thereby saving tokens and improving response accuracy.
Each Model Context Protocol (MCP) server connected to your Claude Code environment adds to your active context, consuming tokens even if not actively used. To maintain efficiency, enable only the MCP servers that are directly necessary for your current task. Regularly reviewing and disabling unneeded connections can lead to substantial token savings, as it reduces the amount of information Claude needs to process in each interaction.
Engaging in a back-and-forth dialogue with Claude, where each question is a separate message, rapidly increases token consumption. A more efficient approach is to combine multiple questions or instructions into a single, comprehensive prompt. This method reduces the number of times Claude has to re-process the entire conversation history, leading to significant token savings and often yielding more coherent and complete responses
Before diving into complex tasks, utilize Claude's plan mode. This feature allows Claude to strategize and outline an approach without executing code or generating extensive outputs, thus avoiding token expenditure on trial-and-error. By thinking through the task beforehand, Claude can develop a more direct and token-efficient execution path, saving resources in the long run.
Over time, conversations can become lengthy and redundant. The" /compact "command is an invaluable tool for compressing your conversation history. It intelligently summarizes and condenses previous exchanges, freeing up context space without losing critical information. Regular use of" /compact "ensures your sessions remain lean and token-efficient, especially during extended projects.
Not all tasks require the most powerful and token intensive models like Opus. For simpler or trivial operations, opt for more cost-effective and faster models such as Sonnet. Understanding the capabilities and token costs associated with different Claude models allows you to make informed decisions, reserving premium models for complex challenges where their advanced reasoning is truly indispensable.
Visibility into your token consumption is a powerful motivator for optimization. By setting up and regularly checking the Claude Code status line, you can see the real-time token cost of each task. This immediate feedback fosters a natural tendency to optimize your prompts and interactions, making you more mindful of token efficiency and encouraging better prompting habits.
