> For the complete documentation index, see [llms.txt](https://docs.americanspend.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.americanspend.com/data-practices.md). # Data practices How American Spend collects, protects, and publishes data. How we collect, protect, and publish data is documented in the [Privacy Policy](https://www.americanspend.com/privacy/), with usage terms in the [Terms of Service](https://www.americanspend.com/terms/) and important notices in the [Disclaimer](https://www.americanspend.com/disclaimer/). Data is licensed at the source. All personally identifiable information is removed before the data reaches American Spend. Records are aggregated across cohorts large enough to prevent re-identification. Individuals are never identifiable in anything we publish, and individual transaction details are never sold. Nothing here is financial, investment, legal, tax, or accounting advice. Figures are estimates, not a census of the American economy. Merchant mappings and category assignments are methodological choices and may be revised. Historical figures may be revised as coverage improves. Commercial use of the data products requires a license. There is no right to resell, redistribute, or build a derivative dataset from the data without authorization. A certification or audit report that is not published on the site is not something to infer. For privacy questions write to . For counsel, . --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://docs.americanspend.com/data-practices.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.