# Sources

The **Sources** section defines which external data is made available to the AI agent as contextual information.

Sources are **read-only** and are automatically added to the agent’s context during execution.\
They do **not replace input parameters**, but **augment** them with additional data the agent can reason over.

***

### Source types

<table><thead><tr><th width="188">Source type</th><th>Description</th></tr></thead><tbody><tr><td><strong>Dataclips</strong></td><td>Datasets created within the Any2Info platform.</td></tr><tr><td><strong>Dataflows</strong></td><td>Dataflows within the Any2Info platform, used as tools.</td></tr><tr><td><strong>Files</strong></td><td>Uploaded documents such as PDF, DOCX, TXT, or other supported formats.</td></tr><tr><td><strong>Vector Stores</strong></td><td>Indexed data stored in vector storage, optimized for semantic search and retrieval.</td></tr></tbody></table>

***

### Tool calling

**Tool calling** is the mechanism by which an AI agent can actively invoke an external function or system during a conversation or task — not just generate text.

#### Supported tools

* **Dataclips**
* **Dataflows**
* **Files (search)**
* **Web (search)**

#### Importance of descriptions

For correct tool usage, **clear descriptions are critical**.\
The AI relies heavily on descriptions to understand **when** and **how** to use tools and how to map inputs and outputs correctly.

This applies to:

* **Dataclips** – Each dataclip has a *Description* field explaining its content and purpose
* **Dataflows** – Each dataflow has a *Description* field explaining what it does
* **Event parameters** – Each parameter includes a *Description* field describing its meaning and usage

Well-written descriptions significantly improve the agent’s ability to:

* Select the correct tool
* Populate parameters correctly
* Execute actions reliably

***

### Dataclips

#### What is it?

A (live) dataset available within the Any2Info platform (ERP, CRM, SQL, API, etc.).

#### What does it provide to the agent?

It supplies the AI with **up-to-date, structured data** to reason with.

#### Examples

* Relationships (AccountID, name, address)
* Articles (ArticleID, price, stock)
* Projects, orders, employees

#### Role in relation to agents

Dataclips answer the question:\
\&#xNAN;**“What exists in my systems?”**

Agents use dataclips to:

* Perform fuzzy matching
* Find IDs
* Validate user choices
* Prevent hallucinated input

***

### Dataflows

#### What is it?

An action or operation within the Any2Info platform, such as:

* Create
* Update
* Sync
* Export
* Trigger

#### What does it provide to the agent?

Dataflows are **“the buttons the AI can press to make things happen.”**

#### Examples

* Create a Synergy document
* Create a Synergy request
* Create a Synergy request with a document
* Send an email
* Download a PDF

#### Role in relation to agents

Dataflows answer the question:\
\&#xNAN;**“What is the agent allowed to DO?”**

***

### Files

#### What is it?

Concrete documents or media passed into an AI call.

#### Examples

* PDFs
* Word documents
* Excel files
* Images
* Scans
* Transcripts

#### What does it provide to the agent?

Files are the **primary sources** that must be read, interpreted, or analyzed.

From files, the AI can:

* Extract text
* Read amounts and values
* Interpret rules and clauses
* Understand document context

#### Ideal use cases

* Quotations
* Invoices
* Inspection reports
* Contracts

#### Role in relation to agents

Files represent:\
\&#xNAN;**“Reality captured in documents.”**

***

### Vector stores

#### What is it?

An indexed (external) knowledge base built on stored data using embeddings.

#### Typical contents

* Manuals
* Contracts
* Product documentation
* Procedures
* Historical cases
* Knowledge articles

#### What does it provide to the agent?

Vector stores give the AI **semantic memory**.

This enables:

* Meaning-based search instead of exact keyword matching
* Retrieval Augmented Generation (RAG)
* Policy enforcement
* Explanations and guidance
* Consistent answers

#### Role in relation to agents

Vector stores answer the question:\
\&#xNAN;**“What does the organization know?”**


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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://academy.any2info.com/any2info-academy/no-code-platform/ai-studio/create-agent/sources.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.