> 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/mcp-methods/model-facts.md).

# Model facts

coverage and panel.

### coverage

Per-day completeness of the data. `start_date` and `end_date` are optional. The latest day on a spend result is the day to treat as now. A window that reaches the newest days is served from the data that has arrived, and those newest days can still move as late transactions come in.

Checking coverage costs nothing, with or without an account.

### panel

The model size, and the date that figure describes. The snapshot is written monthly. When it has not been computed, the call says so and there is no figure to show.

Distinct accounts are not people. For a byline, the published figures are $1.2 trillion of annual consumer spend tracked, 2 billion transactions indexed per month, 150 million or more monthly active accounts, and 1 million merchant locations. For the live date range and the live model size, use these two tools.


---

# 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/mcp-methods/model-facts.md?ask=<question>&goal=<user_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.