> For the complete documentation index, see [llms.txt](https://docs.tabnine.com/main/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.tabnine.com/main/administering-tabnine/managing-your-team/context-engine/assets.md).
# Assets
The Context Engine Assets page in the Admin Console catalogs what you have produced from the Context Engine
To see what Context Engine has produced from your code, open the Context Engine Assets page.
This page catalogs all the generated content from the Context Engine as useful structured outputs from your repositories. When you roll Context Engine out to new codebases, you can return here to confirm that new assets appear and are associated with the correct teams.
At the top of the page, you can review the metrics that show the number of 1) connected data sources, 2) generated assets, 3) existing asset types, and 4) data sources for each type.
To understand which kinds of assets you have, look at the “Data Sources per Type” summary. Check counts for types such as Service Summaries and OpenAPI Specs to verify that the right analyzers are active.
To narrow the asset list, use the filters under Metrics to select a data source, asset type, or team.
If you have recently enabled Context Engine and see no assets, wait for runs to complete. If assets still do not appear after successful runs, adjust the filters or review your analyzer configuration.
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# 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.tabnine.com/main/administering-tabnine/managing-your-team/context-engine/assets.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.
