# Agent Web Search Skill

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## Web Search

Web search lets AI provide up-to-date, real-world information that isn't in its training data, making answers more accurate and relevant. Being able to choose between AI models allows users to tailor responses based on strengths—like reasoning, speed, or integration with specific services. Together, they boost flexibility, precision, and trust in the AI’s output.

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## **Importance of Web Search in AI**

### **Up-to-Date Information**

AI models are trained on data up to a certain point. Web search lets the AI access current events, pricing, live documentation, or recent updates that aren't part of its training.

### Fact Verification

Helps **verify facts**, cross-check claims, and avoid hallucinated or outdated answers.

### Niche or Local Queries

Essential for **location-specific** or **specialized** information (e.g. Romanian tax law changes, product availability, or business hours).

### Source Transparency

Web search allows AI to cite **specific sources**, increasing **user trust** and **accountability**.

## [Web Search Setup Video](https://youtu.be/7N5nPf3e0GA)

{% embed url="<https://youtu.be/7N5nPf3e0GA>" %}


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# Agent Instructions: 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:

```
GET https://docs.raiaai.com/raia-cx/agent-skills/agent-web-search-skill.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.
