Practical recipes for DSL and Data Mapper patterns that come up constantly in real builds. Each pattern includes a use case and a working example you can adapt.

For the full function references, see the DSL Reference and the Data Mapper Reference.

Data Mapper Patterns

Omit null or empty keys from a payload

APIs often reject requests with null fields. Use EVAL() with $FILTER to build an object and strip out any keys that are null or empty before sending.

Use case: Building a calendar event payload where recurrence and location are optional.

1 event_payload:
2   EVAL():
3     args:
4       obj:
5         attendees: data.attendees
6         description: data.event_description
7         end: data.end_time
8         location: data.location_display_name
9         recurrence: data.recurrence
10         start: data.start_time
11         summary: data.title
12     expression: obj.$FILTER(val => val)

If location and recurrence are null, they disappear from the payload entirely.

Transform a list of objects

Use MAP() to reshape each item in an array — rename fields, flatten nested values, or add computed fields.

Use case: Rename API field names to user-friendly names for SDA.

1 accounts:
2   MAP():
3     items: data.raw_accounts
4     converter:
5       account_name: item.Name
6       annual_revenue: item.AnnualRevenue__c
7       owner_email: item.Owner.Email
8       stage: item.StageName

Conditionally include a field

Use CONDITIONAL() to include a field only when a condition is met — useful for building dynamic query filters.

Use case: Only add a date filter to a SOQL query when the user provided a date.

1 query_parts:
2   date_filter:
3     CONDITIONAL():
4       condition: data.close_date_before != "ANY"
5       on_pass: $CONCAT(["CloseDate >= ", data.close_date_before])
6       on_fail: '""'

Merge data from multiple actions

Use MERGE() to combine objects from different action outputs into a single result — useful for compound actions that fetch from multiple sources.

Use case: Combine user data from one action with company data from another.

1 return:
2   output_mapper:
3     enriched_users:
4       MAP():
5         items: data.user_list
6         converter:
7           MERGE():
8             - item
9             - company: data.company_info.name
10               office: data.company_info.hq_address

Map a code to a human-readable label

Use LOOKUP() when an API returns status codes or category IDs that need to be translated for the user.

Use case: Convert ServiceNow incident state numbers to labels.

1 status_label:
2   LOOKUP():
3     key: data.incident.state
4     mapping:
5       '1': "'New'"
6       '2': "'In Progress'"
7       '3': "'On Hold'"
8       '6': "'Resolved'"
9       '7': "'Closed'"
10     default: "'Unknown'"

Build a dynamic URL

Use RENDER() or $CONCAT to construct URLs from dynamic data — for linking back to source records.

Use case: Generate a clickable link to a ServiceNow ticket.

1 ticket_url:
2   RENDER():
3     template: "https://{{instance}}.service-now.com/nav_to.do?uri=incident.do?sys_id={{sys_id}}"
4     args:
5       instance: data.snow_instance
6       sys_id: data.incident.sys_id

Sort results

Use SORT() to order an array by a field.

1 sorted_tickets:
2   SORT():
3     items: data.tickets
4     key: item.created_at

Add reverse: 'true' for descending order.

DSL Patterns

Validate a date is in the future

Use in a slot validation policy to reject past dates.

$PARSE_TIME(value) >= $TIME()

Validate a date is within a range

Check that a date is at least 7 days from now (e.g., for travel booking lead time).

$PARSE_TIME(value) >= $TIME().$ADD_DATE(0, 0, 7)

Check if a value is in a list

Use in for allowlist/blocklist validation.

value in ["US", "CA", "UK", "DE"]

Or with $ANY for more complex matching:

["urgent", "critical", "blocker"].$ANY(level => data.priority.$LOWERCASE() == level)

String formatting and transformation

Chain string functions for normalization:

data.user_input.$TRIM().$LOWERCASE()

Build a full name from parts:

$CONCAT([data.first_name, " ", data.last_name])

Serialize an object to a string

When passing structured data to mw.generate_text_action (which only accepts string input), use $STRINGIFY_JSON:

$STRINGIFY_JSON(data.payload)

Count items matching a condition

data.tickets.$FILTER(t => t.status == "open").$LENGTH()

Conditional logic in compound action switch expressions

Use comparison operators in switch conditions:

1 - switch:
2     cases:
3       - condition: data.amount < 500
4         steps:
5           - action:
6               action_name: auto_approve
7               output_key: approval_result
8       - condition: data.amount >= 500 AND data.amount < 5000
9         steps:
10           - action:
11               action_name: manager_approval
12               output_key: approval_result
13     default:
14       steps:
15         - action:
16             action_name: vp_approval
17             output_key: approval_result

Combined Patterns

These patterns use both DSL expressions inside Data Mappers.

Dynamic message with data from multiple sources

Use RENDER() (mapper) with DSL expressions in the args:

1 message:
2   RENDER():
3     template: |
4       Hi {{name}}, your {{request_type}} request ({{id}}) has been {{status}}.
5       {{comment}}
6     args:
7       name: data.user.first_name
8       request_type: data.request.type.$TITLECASE()
9       id: data.request.display_id
10       status: data.approval_result.status.$LOWERCASE()
11       comment:
12         CONDITIONAL():
13           condition: data.approval_result.denied_by[0].comment != null
14           on_pass: $CONCAT(["Reason: ", data.approval_result.denied_by[0].comment])
15           on_fail: '""'

Filter and transform in one step

Use DSL $FILTER inside a mapper MAP():

1 active_high_value_accounts:
2   MAP():
3     items: data.accounts.$FILTER(a => a.status == "Active" AND a.annual_revenue > 100000)
4     converter:
5       name: item.name
6       revenue: item.annual_revenue
7       owner: item.owner_email