Paste This Into Claude Code, Never Run Out Of Tokens Again

The Root Cause of Token Overuse00:01:00

Most token consumption isn't from your input, but from the model re-reading your entire conversation history every time you send a new message. Because LLMs have no memory, every interaction compounds, causing costs to balloon rapidly in long sessions.

The Golden Rule: Clear Your Session00:03:00

The most effective way to save tokens is using the /clear command. By resetting the session when starting a new task, you stop the AI from re-processing accumulated history. Use /rename and /resume if you need to keep previous work accessible.

Common Traps: Switching Models and Settings00:04:30

Changing your model (e.g., Opus to Sonnet), adjusting effort levels, or enabling plugins mid-session invalidates your cache. This forces the model to reprocess the entire context at full price, which is often 10 times more expensive than cache reads.

Optimizing Tool Usage and Output00:06:27

Stop your agent from reading unnecessary verbose command outputs by implementing a filter. Additionally, disable unused tools via the tool menu to prevent the agent from loading unnecessary instruction manuals into every session.

Sub-agent Strategy and Scheduled Tasks00:10:12

Sub-agents only save money if the session continues for many turns. Be cautious of background scheduled tasks; if they trigger infrequently (outside the 1-hour cache window), they will re-process your entire context at full cost every time.

What to Avoid and Monitoring Tools00:14:42

Avoid common myths: short prompts aren't as important as file management. Instead, use /context and /usage to audit what is consuming your tokens. Always convert PDFs to text files, as images and PDFs cause significant redundant token charges.