> For the complete documentation index, see [llms.txt](https://raia2.gitbook.io/raia/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://raia2.gitbook.io/raia/raia-cx/agent-skills/agent-external-retriever-skill.md).

# Agent External Retriever Skill

<figure><img src="https://1905631084-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FEwGkQrKpAAj0jhmC3fkJ%2Fuploads%2Ftkc4WoiSqFG68ky0cry1%2Fimage.png?alt=media&amp;token=39890823-b869-44df-895d-67e61333213d" alt=""><figcaption></figcaption></figure>

## Ability to have multiple Retrievers per Agent

You have the ability to add and setup multiple External Retrievers per AI Agent.

<figure><img src="https://1905631084-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FEwGkQrKpAAj0jhmC3fkJ%2Fuploads%2FDYKKr7IbGt92Suc1WCIE%2Fimage.png?alt=media&amp;token=005e17f0-d779-48e6-8ede-33359bcad23c" alt=""><figcaption></figcaption></figure>

## Ability to choose the Retriever Type

Choosing an external retriever type, like Pinecone, allows your AI system to efficiently access and query large-scale vector databases for relevant information. This enhances retrieval accuracy, performance, and scalability, especially in applications requiring fast semantic search or context-aware responses.

<figure><img src="https://1905631084-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FEwGkQrKpAAj0jhmC3fkJ%2Fuploads%2F7jMdrOfse24uMu50qj2j%2Fimage.png?alt=media&amp;token=042f0164-a9c5-4f0a-95b8-c4500817471d" alt=""><figcaption></figcaption></figure>

## Customizable Retriever Name

You're able to freely customize the Retriever name for whatever purpose.

<figure><img src="https://1905631084-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FEwGkQrKpAAj0jhmC3fkJ%2Fuploads%2FCCToW74u3ksvP8GspTmd%2Fimage.png?alt=media&amp;token=8a81f9ac-743d-4c67-b007-dfcc991ff982" alt=""><figcaption></figcaption></figure>

## API Key

An API Key is essential in the external retriever setup because it securely authenticates your connection to third-party services or databases. It ensures only authorized access to external content sources, enabling your AI to retrieve accurate, real-time information while protecting sensitive data.

<figure><img src="https://1905631084-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FEwGkQrKpAAj0jhmC3fkJ%2Fuploads%2Fbvn0qizx2bDZKwMjWl60%2Fimage.png?alt=media&amp;token=76e35df1-b42a-4aec-a2e5-e50ce42f2f59" alt=""><figcaption></figcaption></figure>


---

# 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 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://raia2.gitbook.io/raia/raia-cx/agent-skills/agent-external-retriever-skill.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

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.
