Check whether pasted text fits a language-model context window using the same UTF-8 byte heuristic as the token estimator.
How it works
Token count is estimated as ceil(utf8Bytes / 4) ā a common English approximation. The tool compares that estimate to a preset context limit (32k, 128k, or 200k tokens) and reports percent used plus a yes/no fit flag.
When to use it
Preflight long prompts before API calls, size RAG context against model limits, or explain why a document must be chunked for Claude, GPT, or other chat models.
Limitations
Real tokenizer counts differ by model and language; treat results as planning estimates, not billing numbers. Does not account for message overhead, tool definitions, or multimodal tokens.
Example
A few paragraphs of English text against a 128k limit typically shows a low percent used and fits = Yes; a full book pasted in may exceed smaller windows.