How to Fix 'Context Length Exceeded' Errors in LLM API Requests

When an LLM API returns a 'context length exceeded' error, the fix requires understanding that total context includes system instructions, conversation history, messages, files, tool definitions, tool results, and the output budget combined. Developers should first identify the model and measure each component's token usage before making any reductions. Safe trimming steps include removing duplicate system rules, irrelevant conversation history, redundant RAG chunks, unused tool definitions, and oversized tool results. Critical facts, accepted decisions, and mandatory constraints should be preserved, with large data stored outside the prompt rather than discarded. After resizing the request, both the absence of the error and the completeness of the response should be verified to ensure nothing essential was lost.