# Table Metadata

Table metadata in Actian AI Analyst gives AI Agents the context they need to generate accurate and trusted answers from your data.

Actian AI Analyst supports two types of metadata:

* **Table-level metadata:**\
  High-level details about the table, including its purpose, usage, and any common pitfalls.
* **Column-level metadata:**\
  Details about each column, such as its data type, semantic type, description, and business rules.

### Why is Metadata Important?

* AI Agents use metadata to understand your data’s meaning and business context.
* The more complete and accurate your metadata is, the better the AI Agent’s responses and SQL generation will be.
* Missing or unclear metadata may result in less relevant or incorrect answers.

{% content-ref url="/pages/i4yX4YZhsTYC8Vzof9Pp" %}
[Manage metadata in the UI](/connections/table-metadata/manage-metadata-in-the-ui.md)
{% endcontent-ref %}

{% content-ref url="/pages/5KJLwd3W1Eu3sDHQMwlA" %}
[Import metadata using YAML](/connections/table-metadata/import-metadata-using-yaml.md)
{% endcontent-ref %}


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Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.wobby.ai/connections/table-metadata.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
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.