Structured Outputs

Understand what structured outputs are, why they matter, and how to use them in Lyzr Agents.

In Lyzr, Structured Outputs allow an agent’s response to be returned in a machine-readable format such as JSON. Instead of free-form text (which is harder to parse and act upon), structured outputs give predictable formats that downstream systems and tools can work with directly.

This is especially important when integrating Lyzr agents into larger workflows or automation systems.

Why Structured Outputs Matter

Machine Interoperability

Structured responses (like JSON) allow easy integration with tools, databases, dashboards, and APIs.

Predictable Parsing

Downstream tasks don’t need to rely on fragile regex or NLP to extract meaning — the format is known and constant.

UI Rendering

Structured outputs can be displayed directly in tables, charts, or UI components inside Lyzr Studio or external apps.

Validation & Error Handling

You can define required fields, types, or even schemas to validate outputs and catch hallucinations early.

Example Use Cases

Lead Scoring Agent

{
  "lead_name": "John Doe",
  "score": 87,
  "confidence": "High"
}

Tech Support Ticket Generator

{
  "issue": "Login not working",
  "urgency": "High",
  "assigned_to": "[e-mail]"
}

Email Generator

{
  "subject": "Meeting Reminder",
  "body": "This is a reminder for our meeting at 3 PM.",
  "tone": "Formal"
}

How to Use Structured Outputs in Lyzr Studio

Agent Setup

In the Agent creation form, scroll down to the “Expected Output Format” section. Toggle Structured Output to ON.

Define Structure

Provide a sample JSON or a schema-like format.

Example:

{
  "name": "string",
  "score": "integer",
  "recommendation": "string"
}

Agent Prompting

Guide the agent to respond only in this structure. You can add instructions like:

Return your answer in the following JSON format. Do not include any extra text.

Validation

Lyzr can automatically validate if the agent output matches the expected structure. If not, retries or error prompts can be triggered.

Best Practices

Tip	Description
Be explicit	Clearly instruct the agent to return only JSON, with no surrounding explanations.
Retry failures	If the output doesn’t match the schema, implement a fallback or retry with clarification.
Keep it minimal	Only include necessary fields in the structure to avoid verbosity.
Test edge cases	Try empty inputs or malformed examples to validate agent behavior.

When Not to Use Structured Outputs

While powerful, structured outputs are not always necessary:

• Use free-form outputs for conversational agents, creative writing, or open-ended analysis.
• Use structured outputs for integrations, data transformations, or post-processing workflows.

Summary

Feature	Value
Format	JSON, tables, key-value
Best for	Automation, parsing, UI rendering
Setup	Enabled in agent creation or API
Key Benefit	Makes agent responses usable in downstream logic

Using Structured Outputs in Lyzr transforms your agents from conversational tools to modular, programmable, and integrable components suited for real-world applications.