Structured Inputs

When automating form-heavy workflows, you often need to pass many related fields. Instead of creating a separate variable for each field, you can pass structured JSON objects and access nested properties directly in your prompts.

The Problem

Consider a loan document with a “Section G” containing many fields. Without structured inputs, you’d need to define separate variables for each:

{section_g_cost}
{section_g_account_number}
{section_g_customers_1_id}
{section_g_customers_1_name}
{section_g_customers_1_description}
... (many more)

This becomes unwieldy and error-prone.

The Solution: Nested Access

With structured inputs, you can pass a single JSON object and access nested properties directly:

{section_g.cost}
{section_g.account_number}
{section_g.customers[0].id}
{section_g.customers[0].name}
{section_g.customers[1].description}

Then when creating a run, you simply pass:

TypeScript
Python

const { data: run } = await client.runs.create({
  workflow_id: 'workflow-uuid',
  input_values: {
    section_g: {
      cost: 50000,
      account_number: 'ACC-12345',
      customers: [
        { id: 'C001', name: 'John Doe', description: 'Primary applicant' },
        { id: 'C002', name: 'Jane Doe', description: 'Co-applicant' }
      ]
    }
  }
});

run_data = RunCreate(
    workflow_id='workflow-uuid',
    input_values={
        'section_g': {
            'cost': 50000,
            'account_number': 'ACC-12345',
            'customers': [
                {'id': 'C001', 'name': 'John Doe', 'description': 'Primary applicant'},
                {'id': 'C002', 'name': 'Jane Doe', 'description': 'Co-applicant'}
            ]
        }
    }
)

Syntax Reference

Dot Notation

Access object properties with .:

{user.email}
{config.settings.theme}

Bracket Notation (Arrays)

Access array elements by index:

{customers[0]}
{items[2].name}

Bracket Notation (Special Keys)

For keys with special characters, use bracket notation with quotes:

{data['special-key']}
{headers["Content-Type"]}

Combining Notations

Chain any combination for deeply nested structures:

{form.sections[0].fields['field-name'].value}
{response.data.users[0].profile.settings['notification-preferences']}

Works Across All Variable Types

Structured access works consistently for all three variable types:

Type	Syntax	Example
Input	`{var.path}`	`{patient.demographics.dob}`
Sensitive	`{$var.path}`	`{$credentials.api_key}`
Runtime	`{{var.path}}`	`{{extracted_data.invoice_id}}`

Need these delimiters to appear literally instead of resolving as variables? Escape the opening delimiter:

\{customer_name} renders as literal {customer_name}
\{{current_status}} renders as literal {{current_status}}
\{$support_pin} renders as literal {$support_pin}

This works in workflow prompt text and in input values you pass at run start.

Sensitive Inputs Example

// Workflow prompt uses: {$credentials.username} and {$credentials.password}

const { data: run } = await client.runs.create({
  workflow_id: 'workflow-uuid',
  sensitive_input_values: {
    credentials: {
      username: 'admin',
      password: 's3cr3t'
    }
  }
});

Runtime Values Example

When a focused_action sets a runtime value as an object:

"Use focused_action to extract the invoice details and save them as {{invoice}}"

You can then access nested properties in subsequent steps:

"Enter the invoice number {{invoice.number}} in the search field"
"Verify the amount matches {{invoice.line_items[0].amount}}"

Using Refs in Chains

When running multiple workflows in a session chain, you can use $ref to pass outputs from previous steps as inputs to later steps. Refs work inside structured inputs, allowing you to build complex input objects from prior outputs.

Basic ref inside structured input

steps: [
  {
    workflow_id: 'extract-workflow',
    session_alias: 'extract',
    inputs: { document_id: '12345' }
    // This step outputs: { result: { customer: { name: 'John', email: 'john@example.com' } } }
  },
  {
    workflow_id: 'process-workflow',
    session_alias: 'process',
    inputs: {
      // Use the entire extracted object
      customer_data: { $ref: 'extract.outputs.result.customer' }
    }
  }
]

Building structured inputs from multiple refs

You can mix refs with literal values anywhere in the structure:

inputs: {
  data: {
    // Ref to a nested field
    query: { $ref: 'step1.outputs.result.query' },
    // Ref to an array element
    first_keyword: { $ref: 'step1.outputs.result.keywords[0]' },
    context: {
      // Another ref
      summary: { $ref: 'step1.outputs.result.summary' },
      // Literal value mixed in
      priority: 'high'
    }
  }
}

Cyberdesk keeps $ref values as references when you create the run, validates them against the destination input schema when possible, and resolves them at execution time before the receiving workflow uses them. Your workflow prompt receives the actual values, not the $ref syntax.

For more on refs and chains, see Sessions and Chains.

Error Handling

Type Mismatches (Fails the Run)

If you try to access a nested property on a value that isn’t an object or array, the run fails immediately with a clear error:

// Prompt: {section_g.cost}
// Input: {"section_g": "just a string"}
// ❌ Error: Cannot access path '.cost' on input_values['section_g'] because it is a str, not an object or array

This catches configuration errors early, saving you time and usage costs.

Missing Fields (Uses `EMPTY`)

If a nested path simply doesn’t exist, it’s replaced with the __EMPTY__ sentinel value (same behavior as regular empty inputs):

// Prompt: {section_g.optional_field}
// Input: {"section_g": {"cost": 500}}
// Result: __EMPTY__ (field doesn't exist)

This allows workflows to gracefully handle optional nested fields. If you want to intentionally blank out a field that already has a value, use __CLEAR__ instead of __EMPTY__.

Array Out of Bounds

Accessing an array index that doesn’t exist is treated as missing (not a type error):

// Prompt: {customers[5].name}
// Input: {"customers": [{"name": "John"}]}
// Result: __EMPTY__ (only 1 item in array)

Backward Compatibility

Existing workflows continue to work exactly as before:

{variable} with a string value → replaced with the string
{variable} with an object/array value (no nested access) → JSON stringified

// Prompt: {my_data}
// Input: {"my_data": {"a": 1, "b": 2}}
// Result: {"a": 1, "b": 2}  (stringified JSON)

Best Practices

Group Related Fields

Organize related inputs into logical objects (e.g., patient, billing, shipping) rather than dozens of flat variables.

Use Consistent Structures

Define a standard schema for your inputs across workflows. This makes SDK integration easier and reduces errors.

Validate Early

Cyberdesk validates type mismatches at run start. Structure your inputs correctly to catch errors before execution begins.

Handle Optional Fields

Missing nested fields become __EMPTY__. Design your prompts to handle this gracefully for optional data.

Real-World Example: Healthcare Form

Fill out the patient intake form:

**Demographics**
- First Name: {patient.demographics.first_name}
- Last Name: {patient.demographics.last_name}
- DOB: {patient.demographics.date_of_birth}
- SSN: {$patient.ssn}

**Insurance**
- Provider: {patient.insurance.provider}
- Policy Number: {patient.insurance.policy_number}
- Group ID: {patient.insurance.group_id}

**Emergency Contacts**
- Primary Contact: {patient.emergency_contacts[0].name}
- Primary Phone: {patient.emergency_contacts[0].phone}
- Secondary Contact: {patient.emergency_contacts[1].name}
- Secondary Phone: {patient.emergency_contacts[1].phone}

TypeScript
Python

const { data: run } = await client.runs.create({
  workflow_id: 'patient-intake-workflow',
  input_values: {
    patient: {
      demographics: {
        first_name: 'John',
        last_name: 'Doe',
        date_of_birth: '1985-03-15'
      },
      insurance: {
        provider: 'Blue Cross',
        policy_number: 'BC123456',
        group_id: 'GRP001'
      },
      emergency_contacts: [
        { name: 'Jane Doe', phone: '555-0101' },
        { name: 'Bob Smith', phone: '555-0102' }
      ]
    }
  },
  sensitive_input_values: {
    patient: {
      ssn: '123-45-6789'
    }
  }
});

run_data = RunCreate(
    workflow_id='patient-intake-workflow',
    input_values={
        'patient': {
            'demographics': {
                'first_name': 'John',
                'last_name': 'Doe',
                'date_of_birth': '1985-03-15'
            },
            'insurance': {
                'provider': 'Blue Cross',
                'policy_number': 'BC123456',
                'group_id': 'GRP001'
            },
            'emergency_contacts': [
                {'name': 'Jane Doe', 'phone': '555-0101'},
                {'name': 'Bob Smith', 'phone': '555-0102'}
            ]
        }
    },
    sensitive_input_values={
        'patient': {
            'ssn': '123-45-6789'
        }
    }
)

This approach transforms 15+ separate variables into a clean, hierarchical structure that mirrors your actual data model.

Getting started

SDK Guides

Cyberdriver

Workflow Prompting

Webhooks

Concepts

Additional Details

The Problem

The Solution: Nested Access

Syntax Reference

Dot Notation

Bracket Notation (Arrays)

Bracket Notation (Special Keys)

Combining Notations

Works Across All Variable Types

Sensitive Inputs Example

Runtime Values Example

Using Refs in Chains

Basic ref inside structured input

Building structured inputs from multiple refs

Error Handling

Type Mismatches (Fails the Run)

Missing Fields (Uses `EMPTY`)

Array Out of Bounds

Backward Compatibility

Best Practices

Group Related Fields

Use Consistent Structures

Validate Early

Handle Optional Fields

Real-World Example: Healthcare Form

Getting started

SDK Guides

Cyberdriver

Workflow Prompting

Webhooks

Concepts

Additional Details

Documentation Index

​The Problem

​The Solution: Nested Access

​Syntax Reference

​Dot Notation

​Bracket Notation (Arrays)

​Bracket Notation (Special Keys)

​Combining Notations

​Works Across All Variable Types

​Sensitive Inputs Example

​Runtime Values Example

​Using Refs in Chains

​Basic ref inside structured input

​Building structured inputs from multiple refs

​Error Handling

​Type Mismatches (Fails the Run)

​Missing Fields (Uses __EMPTY__)

​Array Out of Bounds

​Backward Compatibility

​Best Practices

Group Related Fields

Use Consistent Structures

Validate Early

Handle Optional Fields

​Real-World Example: Healthcare Form

The Problem

The Solution: Nested Access

Syntax Reference

Dot Notation

Bracket Notation (Arrays)

Bracket Notation (Special Keys)

Combining Notations

Works Across All Variable Types

Sensitive Inputs Example

Runtime Values Example

Using Refs in Chains

Basic ref inside structured input

Building structured inputs from multiple refs

Error Handling

Type Mismatches (Fails the Run)

Missing Fields (Uses `EMPTY`)

Array Out of Bounds

Backward Compatibility

Best Practices

Real-World Example: Healthcare Form