Section 3: Define Properties and Data Types

What Are Properties?

Properties are the building blocks of your agent’s output.

Each one defines a field of data you want to extract, classify, summarize, or generate.

Think of them as your columns in a table or fields in a form — each property has a defined type, an associated tool, and a prompt that tells the AI what to do.

Standard Property Types

Below is a breakdown of the core property types used when building agents:

Property Type	Best For	Notes
File	Uploading files for reference.	Upload and manage files from PDFs to CSVs and more.
Text	Free-form answers, summaries, notes	Enables AI Citations; use when flexibility is needed
Number	Prices, interest rates, percentages, counts	Enables AI Citations; formats automatically (e.g. currency, decimals)
Single Select	Choosing one option from a fixed list	Constrains outputs; supports routing logic and sub-workflows
Multi-Select	Selecting multiple discrete options from a fixed list.	Useful for inspections, risks, features, etc., any time you there is a defined list of outputs with multiple options.
Collection	Tables or sub-rows within a document/workflow	Enables complex, structured outputs (e.g., line items, photo logs)
JSON	Structured multi-value extraction in one pass	Best for grouped fields, improved accuracy, token efficiency
Reference	Connect other agents to this one to enable more structured workflows.	Best when you need to share data across agent entities, and connect workflows together.
URL	Document links, sources, web references	Typically populated by manual input, or web search.
Page Splitter	Split files into a collection, with each page becoming its own entity/row.	Best when dealing with very large PDF or Excel files, in order to make their extraction and QA more manageable.

What Is Grounding?

Grounding ensures that AI-generated outputs are backed by specific evidence from the source document.

In V7 Go, grounding appears as AI citations — clickable highlights that show exactly where in the file the AI found its answer.

This is essential for:

Trust & auditability
Human-in-the-loop QA
Legal, compliance, and financial workflows

Where AI Citations Work Today

Currently, AI citations are supported for the following property types:

Property Type	Grounding Support	Notes
Text	✅ Yes	Most common use case
Number	✅ Yes	Works well for prices, and numeric values.
JSON	🔶 Partial	Supported if you cite in-text JSON values; better control using Python downstream
Collections	🔶 Partial	Citations are available when pointing to a Collection as an Input (e.g. File Bundle) but do not currently work when used as a Collection output.
Selects	❌ Not Yet	On the roadmap — currently no citations
Multi-Select	❌ Not Yet	Same as above

What’s Coming: “Grounding Everywhere”

Citations for Collections (input bundles) are actively being developed
Single/Multi Select grounding is on the roadmap
Goal: Grounding available everywhere, across all tools and document types

Tips for Grounding-First Prompts

If grounding is important for a field:

Use Text or Number property types
Write clear, narrow prompts that focus on specific terms
Avoid combining too many concepts in one prompt

General Tips

Start simple: Most POCs begin with Text, Number, Single Select, Multi-Select and Collection properties for core fields.
Add complexity as needed: Use Selects and Collections once field options or document structures are better understood.
Use JSON to avoid conflating similar fields (e.g. Start Date vs. End Date).

Real-world Use Case: Logistics - Purchase Order Processing

Matching Property to Output

Use this mental checklist:

Is the output free-form or structured? → Use Text/Select/Number/Collection
Is there only one correct answer? Or multiple? → Use Single Select or Multi-Select
Do I want multiple related values in one field? → Use JSON
Am I dealing with tabular or repeating data inside a doc? → Use Collection

Key Takeaway

Choose property types that reflect your final output format and improve downstream usability.

The more structured your properties, the more scalable and automated your workflow becomes.