Whitespace tokenization is simple but language rules can differ.
Quick answer
Words are estimated from whitespace-separated tokens and reading time uses a words-per-minute assumption.
Spaces
Words are estimated from whitespace-separated tokens and reading time uses a words-per-minute assumption. In this context, spaces matters because the output should match the task rather than simply produce a file or string. Review the result against the original input and keep an untouched copy when the workflow changes a file.
Punctuation
Words are estimated from whitespace-separated tokens and reading time uses a words-per-minute assumption. In this context, punctuation matters because the output should match the task rather than simply produce a file or string. Review the result against the original input and keep an untouched copy when the workflow changes a file.
Languages
Words are estimated from whitespace-separated tokens and reading time uses a words-per-minute assumption. In this context, languages matters because the output should match the task rather than simply produce a file or string. Review the result against the original input and keep an untouched copy when the workflow changes a file.
Practical example
Use the matching Get Tools Lab Word Counter tool with a small, non-sensitive example first. Confirm the expected result before using a larger or important input.
Privacy and limitations
Processing behavior depends on the tool. Priority browser-local tools identify that behavior on the tool page. A local browser workflow reduces server upload exposure, but it does not remove the need to protect the source file, device and downloaded result.
Related workflow
Open Word Counter. You can also use the related comparison, glossary and topic pages to understand the format and trade-offs.