> For the complete documentation index, see [llms.txt](https://docs.truecaller.com/truecaller-for-business/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.truecaller.com/truecaller-for-business/spam-management/how-is-spam-calculated-on-truecaller.md).

# How is spam calculated on Truecaller?

Truecaller uses a smart algorithm powered by machine learning to help identify spam calls. It doesn’t just rely on the number of spam reports—it looks at a combination of factors.

There is no fixed number of reports that automatically marks a number as spam. Instead, our system analyses overall patterns and behavior over time. This helps us make sure that genuine businesses are not wrongly flagged, while still protecting our users from unwanted or suspicious calls.


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# Agent Instructions
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## Querying This Documentation
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Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
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