claude api prompt too long error

The Claude API relies on a strict context window. If you pass a prompt, system instructions, or an assembly of documents that exceeds this boundary, the API will fail to process the request and throw a 400 bad request error. To get your system back up and running, you must optimise how you measure and manage your input text.

Calculate tokens accurately with Tokenizers

Character counts or word counts are unreliable indicators of prompt length. Claude uses a custom tokenisation method where words are split into sub-word units. To prevent unexpected errors, use the official Anthropic tokenizer library in Node.js or equivalent Python token counting tools in your pipeline. Calculate the exact token count before dispatching the request to ensure it stays well within the model limit.

Implement a sliding window or conversation truncation

For multi-turn conversational agents, the history of messages accumulates rapidly. If you append every past user turn without filtering, your token limit will soon be exhausted. Implement a sliding window algorithm that only retains the most recent 5 to 10 dialogue turns, or prune older messages programmatically when the total token count approaches the model limit.

Set appropriate max_tokens parameters

The max_tokens parameter controls the length of Claude's output, but it also counts towards the total processing limit of the request in some rate-limiting systems. Ensure you are not requesting a massive block that, when combined with your input prompt, exceeds your tier boundaries. Reduce this value if your output requirements are modest.

Offload large documents using prompt caching

If your application requires sending the same reference files or instructions repeatedly, the overhead can quickly trigger size-related errors. Take advantage of Anthropic's prompt caching feature. By caching the heavy static sections of your prompt, you not only reduce latency and cost but also minimise the risk of overloading the context window on subsequent calls. If you are experiencing general system lag during these large requests, check our troubleshooting steps for when Claude is not responding to verify if the latency is local or global.

Handle the error gracefully in your application code

Never let a token limit exception crash your entire application. Wrap your API calls in a try-catch block specifically designed to identify token limit errors. When triggered, write logic to automatically truncate the oldest elements of the message history or alert the user to shorten their input, ensuring that the Claude app won't load or hang indefinitely for the end user.