> For the complete documentation index, see [llms.txt](https://learn.getvectorai.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://learn.getvectorai.com/vector-search/searching-with-vector-ai/chunk-search/how-to-do-multi-step-chunk-search.md).

# How to do multi step chunk search

Multi step chunk search can be useful for users who are:

* Trying to accelerate chunk search 
* Want to capture meaning in one field and then explain in another field 
* Want to match semantics in the field at a broader context-level and then hone in at the chunk level.

![Multi step chunk search](/files/-MZBrZ9DXXR4hIKPI0YE)

Multi-step chunk search can be useful in improving the explainability of general search and are now combined into 1 search endpoint for users.

The multistep chunk search endpoint can be found at `/collection/advanced_multistep_chunk_search`~~.~~   


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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 dynamically by asking a question.

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

```
GET https://learn.getvectorai.com/vector-search/searching-with-vector-ai/chunk-search/how-to-do-multi-step-chunk-search.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
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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.