> For the complete documentation index, see [llms.txt](https://docs.corraldata.com/kb/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.corraldata.com/kb/chat-with-your-data/build-prompts-in-askcorral.md).

# Build Prompts in AskCorral

Have questions about virtually anything in your data? AskCorral has answers. AskCorral trains our AI model on your account’s specific data such as existing schemas, tables, columns, and account-specific context so you get tailored results quickly.

### How it works:

**Use full and well-spelled sentences:** AskCorral functions even if the prompt is low quality (incomplete sentences, spelling, or grammatical errors, etc.) but the results may not be as high quality. Ask simple questions (as if you’re talking to a human) to maximize the chances of getting strong results.

* Worse Example: Show num of sesionns
* Better Example: Show me the number of sessions our website received

**Be specific:** AskCorral has a thorough understanding of your data sources and data points. Asking specific questions is key to ensuring strong and relevant results. Try to stay away from ambiguous questions that a human may have trouble understanding.

* Worse Example: How many sessions?
* Better Example: How many sessions did we get to the marketing website according to Google Analytics?

**Include sources:** Strengthen your question by telling AskCorral which source(s) to pull from, especially when multiple similar sources are connected (i.e., Meta Ads + Google Ads)

* If asking for blended data across multiple sources (i.e., ALL marketing spend), state this in the prompt, too.
* If you’re asking across different systems, hint at the common key or relationship, if known. Example: *"Join Google Ads spend with Salesforce conversions by campaign ID"*

**Include metrics and time frames:** Help AskCorral better understand "performance" and "growth" specific to you. Define it by adding metrics and time frames to your prompt.

* Examples:
  * *"Calculate MoM change in net revenue from Stripe"*
  * *"Compare user churn rate before and after April 1, 2025"*
  * *"By 'engaged users', I mean users with >3 sessions in the last 30 days"*

**Add internal lingo:** Train AskCorral on the nomenclatures and nuances of how your team “talks about data” by utilizing your [custom instructions](https://docs.corraldata.com/kb/chat-with-your-data/add-custom-instructions) in your prompts. Example: *“How many ‘newbie codes’ were distributed to ‘FTU’ compared to how many were redeemed?”*


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# Agent Instructions
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## 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.corraldata.com/kb/chat-with-your-data/build-prompts-in-askcorral.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.