Workflow node reference: control flow and integration nodes

Configure the Start, REST API Call, FlowX Database, Condition, Start and End Parallel, Script, Subworkflow, and End nodes in Integration Designer workflows.

This page describes the control flow and integration nodes you use in Integration Designer workflows. For every node type, see the workflow nodes overview.

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Start node

The Start node is the mandatory first node in any workflow. It defines the input data model and passes this data to subsequent nodes.

Define all required input fields in the Start node to ensure data mapping from processes or user tasks.

Use Workflow Data Models to define structured input and output parameters at the workflow level. Input parameters automatically pre-fill the Start Node from the data model.

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External triggers

SaaS · 5.12

Available on SaaS with FlowX.AI 5.12. This feature is live on managed (SaaS) deployments now. Self-hosted deployments will receive it with the next LTS release family.

A workflow normally runs when something calls it: a process, a parent workflow, or the run button. Turn on an external trigger and it starts on its own, when a webhook is called or an email arrives.

Open the Start node, expand External Triggers, switch Enable trigger on, then choose Webhook or Email and pick the data source that receives the event.

External triggers are available on Output Focused workflows only. Configuring one on another workflow type is rejected.

To run a workflow on a schedule on SaaS, add a schedule to its Start node. See How do I run a workflow on a schedule?. Self-hosted deployments get workflow schedules with the next LTS release. Until then, create a process with a Timer Start Event and call the workflow from it with a Start Integration Workflow action. See Scheduled processes.

Before you can pick a webhook, the webhook data source has to be set to Start a Process/Workflow. A data source set to Resume a Waiting Process is refused, and because Webhook Behavior cannot be changed after the first save, a resume webhook can never be reused here: create a new one. See Webhook Behavior.

The event lands in the data model. Enabling the trigger adds an entity for the incoming event, and turning the trigger off removes it again, so switch it on before mapping anything downstream.

Trigger	Entity	Contents
Webhook	webhookMessage	dateTime, payload, headers
Email	emailMessage	See the email data schema

payload holds the request body as sent, nested structure intact. headers holds each header as a list of strings, so a single-valued header still arrives as a one-element list.

A script node can then read it directly:

var msg = input.webhookMessage;
var order = msg.payload;
output.orderSummary = order.client + " wants " + order.suma + " " + order.detalii.moneda;

Activate the trigger before it accepts anything. Go to Runtime → Manage Triggers and activate it there. The list also shows how many resources each trigger is bound to.

One data source can be bound to several workflows, and a single incoming event then starts all of them. The Manage Triggers list shows this as a resource count above one. Bind a data source to a second workflow only when you mean to run both.

Incoming webhooks

Creating a webhook data source, Webhook Behavior, providers, the URL and its API key

Email trigger

Creating an email trigger data source, filtering, polling, and the email data schema

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How do I run a workflow on a schedule?

SaaS · 6.0

Available on SaaS with FlowX.AI 6.0. This feature is live on managed (SaaS) deployments now. Self-hosted deployments will receive it with the next LTS release family.

Add a schedule to the workflow’s Start node, then activate it in Runtime → Runtime Settings → Schedules. From then on the workflow starts by itself at each fire time, with no process or caller involved.

Schedules are available on Output Focused workflows. A workflow can have up to 50 schedules, and each one needs a name that is unique on that workflow.

1. Add a schedule

   Open the Start node, expand Schedules, and click Add schedule. Click the new schedule card to open the Schedule Workflow dialog, and give the schedule a Name.

2. Set when it fires

   Choose a Timer Type:

   • Date fires once, at the Fire at date and time, entered in your local time.
   • Cycle fires repeatedly. Pick a Format, ISO or Cron, then build the expression with Guided fields or type it under Expression.

   The dialog previews the next fire times in your local time zone. Check them, then click Save.

3. Activate the schedule

   Go to Runtime → Runtime Settings → Schedules, filter Origin by Workflow, and click Activate on the schedule. The workflow must be part of the project’s active build.

Saving a schedule or publishing a build never activates it. A schedule fires only after you activate it on the Schedules page.

Which cycle format should I use?

Format	How it fires	Example	Rules
ISO	Repeats an ISO 8601 interval a set number of times, or indefinitely	R5/P1D: five times, once a day	The interval must be longer than zero, in whole seconds. A Start Time, if you set one, must be in the future.
Cron	Fires on a six-field cron schedule: second, minute, hour, day of month, month, day of week	0 */5 * * * ?: every five minutes	Cron is read in UTC. Set an Active window with a Start and an End: the schedule fires only between them. Macros such as @daily and @hourly also work.

What does a scheduled run receive? A scheduled run doesn’t use the Start node’s test payload. Its input holds three fields that you can map like any other input:

Field	Contents
firedAt	When the run actually started, as an ISO 8601 timestamp
scheduledFor	When the schedule was due, as an ISO 8601 timestamp
triggerName	The name of the schedule that started the run

Where do scheduled runs show up? In Workflow Instances, with the origin Schedule. The run details name the schedule that started it.

How do I stop a schedule? To pause it, click Deactivate on the Schedules page, and click Activate to resume it. To remove it for good, delete it from its card on the Start node. A deleted schedule stops firing immediately, and the deletion can’t be undone.

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REST API Call node

Enables communication with external systems via REST API calls. Supports GET, POST, PUT, PATCH, and DELETE methods. Endpoints are selected from a dropdown, grouped by system.

• Params: Configure path, query, and header parameters.
• Input/Output: Input is auto-populated from the previous node; output displays the API response.

You can test REST API Call nodes independently to validate connections and data retrieval.

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When does a REST API Call node take its failure exit?

A REST API Call node has a success exit and a failure exit. It takes the success exit only for a 2xx response without errors. Everything else takes the failure exit:

• a non-2xx response;
• a timeout, stored as status 408 with data.timeout: true (set the limit with Timeout on the node’s Settings tab, default 10000 ms);
• a connection error;
• a response body declared as JSON or XML that can’t be parsed.

With Allow Retry on, a 408, 429, 500, 502, 503, or 504 is retried first, and the node takes the failure exit only once the retries are used up.

If the call fails and the failure exit isn’t connected, the workflow instance fails with Workflow is missing outgoing sequence. It doesn’t fall through to the success exit.

On both exits the node writes its result under its response key: data (the parsed body), metadata (statusCode and headers), hasError and errorMessage. hasError only flags connection and parsing errors: a 4xx or 5xx with a readable body has hasError: false even though the node took the failure exit, and on a timeout it isn’t set. To branch on the outcome, use the exits or metadata.statusCode, not hasError.

Errors while building the request, such as a failed input mapping or a missing endpoint, don’t use the failure exit. They fail the workflow instance.

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FlowX database node

Allows you to read and write data to the FlowX Database within your workflow.

FlowX Database Documentation

Learn more about FlowX Database operations, collections, and usage

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Condition (Fork) node

Evaluates logical conditions (JavaScript or Python) to direct workflow execution along different branches.

• If/Else: Routes based on condition evaluation.
• One branch per run: The node follows the first branch whose condition passes, or the Else branch. To run branches at the same time, use the Start Parallel and End Parallel nodes.

Use fork nodes to implement business rules, error handling, or multi-path logic.

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Available bindings

Condition expressions have access to the following data bindings:

Binding	Description
input	Workflow input data from the previous node
additionalData.securityDetails	Current user’s identity (username, identifier, details including roles, groups, and attributes from 5.7.0 onward)
additionalData.applicationConfiguration	Configuration parameters from the app build

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Condition examples

JavaScript

// Route based on user identity
additionalData.securityDetails.username === '[e-mail]'

// Route based on configuration parameter
additionalData.applicationConfiguration.featureEnabled === true

// Combine input data with config parameters
input.amount > additionalData.applicationConfiguration.approvalThreshold

// Check user and input together
input.priority === 'high' && additionalData.securityDetails.details.email.endsWith('@company.com')

Python

# Route based on user identity
additionalData["securityDetails"]["username"] == "[e-mail]"

# Route based on configuration parameter
additionalData["applicationConfiguration"]["featureEnabled"] == True

# Combine input data with config parameters
input["amount"] > additionalData["applicationConfiguration"]["approvalThreshold"]

# Check user and input together
input["priority"] == "high" and additionalData["securityDetails"]["details"]["email"].endswith("@company.com")

For details on the securityDetails and applicationConfiguration structure, see Extracting additional data in business rules.

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Calling reusable functions in conditions

SaaS · 5.11

Available on SaaS with FlowX.AI 5.11. This feature is live on managed (SaaS) deployments now. Self-hosted deployments will receive it with the next LTS release family.

Condition expressions can call the reusable functions defined in your project, so branch routing can reuse the same business logic as your processes. Call a function inside a condition using the standard syntax:

JavaScript

// Route on the result of a reusable function
functions.lending.isEligible(input.applicant) === true

Python

# Route on the result of a reusable function
functions.lending.isEligible(input["applicant"]) == True

Each branch condition can call functions, and the node resolves the functions referenced across all of its branches together. Resolution follows the same rules as the Script node: calls resolve from the workflow’s build, a function that calls another function resolves its full call chain, and cross-app calls are matched by app name.

As with Script nodes, reusable functions resolve only in a build context. A draft or test run with no build resolves no functions.

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Start Parallel and End Parallel nodes

Run several steps of a workflow at the same time with a pair of nodes: Start Parallel splits the flow into branches that all run at once, and End Parallel waits for every branch, merges what the branches wrote, and continues. In the node palette they sit under Flow Control as Start Parallel Path and End Parallel Path. Dropped on the canvas, they are named Start Parallel and End Parallel.

These nodes are the only way to run branches concurrently. A Condition (Fork) node evaluates its conditions and follows one branch.

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How do I run steps in parallel?

1. Add a Start Parallel node

   Drag Start Parallel Path from the Flow Control group onto the canvas and connect the previous node to it.

2. Create one sequence per branch

   Draw a sequence from the Start Parallel node to the first node of each branch. Every outgoing sequence is a branch. A branch needs at least one node: the Designer does not let you connect a Start Parallel node straight to an End Parallel or End Flow node.

3. Build each branch

   Add the nodes each branch needs: REST endpoints, scripts, FlowX Database operations, AI nodes, subworkflows, or another Start Parallel node for nested branches.

4. Close every branch on the same End Parallel node

   Connect the last node of every branch to one End Parallel Path node, then connect that node to whatever comes next. An End Parallel node allows a single outgoing sequence.

At runtime all branches run concurrently. The End Parallel node completes when the slowest branch reaches it, so the branch section takes as long as its longest branch, not the sum of the branches.

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What data does each branch see?

Each branch starts with a deep copy of the workflow data as it was when the Start Parallel node ran. Branches work on independent copies: a branch cannot read what another branch writes while they run.

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How are the branches merged?

When a branch reaches the End Parallel node, the keys that branch wrote are merged into the parent data with a recursive deep merge, in the order the branches finish:

• Keys written by only one branch are kept.
• A key written by two branches ends up with the value from the branch that finished last.
• Nested objects are merged key by key, so only the conflicting leaf values are overwritten.
• Arrays and all other non-object values are replaced whole. There is no element-level merge, so two branches cannot each fill a different element of the same array.

Because the merge order depends on which branch finishes last, two branches that write the same key give a non-deterministic result.

Have each branch write to its own key, for example apiResultA, apiResultB and apiResultC, and combine them in a Script node after the End Parallel node.

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What happens when a branch fails?

• A node that fails inside a branch follows the same rules as anywhere else in the workflow. If its failure exit is connected, the branch continues on that path and must still reach the End Parallel node. If the failure exit is not connected, the workflow instance fails.
• When the instance fails, the other branches stop at the next node they reach. Nothing they already executed is rolled back.
• If the branches of one Start Parallel node end on different End Parallel nodes, or one End Parallel node receives branches from two different Start Parallel nodes, the run fails with Missing end parallel gateway and the cause Parallel branches merge failed: missing or incompatible end parallel node.
• A Start Parallel node with no outgoing sequence fails the run with Workflow is missing outgoing sequences.

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Runtime view

Console logging

• Start Parallel node: the Input tab shows the data handed to the branches.
• End Parallel node: the Output tab shows the merged result of all branches.
• Path grouping: the nodes of each branch are grouped by path, so you can follow one branch at a time.

Path timing

• Path time: sum of the execution times of the nodes in that branch.
• End Parallel time: the node’s own processing time plus the longest path time.
• Example: if branch A takes 2s and branch B takes 5s, the End Parallel node completes after 5s plus its own processing time.

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Use cases

Multiple API calls

Call several independent APIs at once instead of one after the other.

Data enrichment

Fetch data from several sources in parallel and combine it afterwards.

Notification broadcasting

Send notifications through several channels (email, SMS, push) at the same time.

Document processing

Process different document types or sections in parallel.

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Limitations

• Same End Parallel node for all branches: every branch of a Start Parallel node must end on the same End Parallel node, and that node allows one outgoing sequence.
• Last-write-wins merge: write to distinct keys per branch and combine them in a Script node afterwards.
• No element-level array merge: you cannot process the first element of an array in one branch and the second in another.
• No cross-branch reads: branches run on independent data copies and cannot see each other’s writes until the merge.
• Nesting is allowed: a branch can contain its own Start Parallel and End Parallel pair.

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Script node

Executes custom JavaScript or Python code to transform, map, or enrich data between nodes.

The node’s output is merged into the workflow data, the same way business rule output is merged into process data: keys the script doesn’t write keep their values, and writing {} to an existing object changes nothing. To clear a key, set it to null. For the full merge rules, see How output is merged into process data.

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Calling reusable functions

SaaS · 5.11

Available on SaaS with FlowX.AI 5.11. This feature is live on managed (SaaS) deployments now. Self-hosted deployments will receive it with the next LTS release family.

A Script node can call the reusable functions defined in your project, the same way a process Business Rule action does. Write the call directly in the node’s code using the standard syntax:

functions.projectName.functionName(input.params)

The Designer reads the function calls from your script and links the node to those functions automatically, so there is no separate step to register a reference. The linked functions also appear on each function’s Usages tab, and removing the node clears those usage entries.

Function calls resolve from the app version that the workflow runs in, and a function that calls another function resolves its full call chain. Functions defined in a different app are matched by their app name, so cross-app calls work the same way they do in processes.

Reusable functions resolve only in a build context. The Script node’s Test modal resolves them when you run it against a selected build; a draft or preview run with no build in context resolves no functions, so calls to functions.* return no result until a build is selected.

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Testing a script in isolation

A Script node ships with a Test modal that lets you exercise the script against sample input without running the full workflow. Open it with the expand icon at the top-right corner of the code editor, next to the expand/collapse chevron.

The modal has three side-by-side panels:

Panel	Purpose
Input	JSON input passed to the script. Load from a past individual node run or from a past workflow run via the input selector.
Code	The script body. Inline warnings are surfaced as you type. Includes Save and Test buttons.
Output	The JSON returned by the script after running Test. Runtime errors are shown here.

The Test button runs the current contents of the Code panel, even if you have not clicked Save yet. Use this to iterate on a fix without committing changes to the Script node.

Runs triggered from the Test modal are excluded from the Console log History panel, because they may be running unsaved code.

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Run instance IDs in the Logs tab

The Logs tab of a workflow run displays the node run instance ID alongside the workflow instance ID for each Script node execution. A copy button is rendered next to every instance ID. Use this to grab a node-run identifier and paste it into the Test modal’s input selector to replay the exact past run.

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Subworkflow node

The Subworkflow node allows you to modularize complex workflows by invoking other workflows as reusable subcomponents. This approach simplifies process design, promotes reuse, and simplifies maintenance.

1. Add a Subworkflow Node

   Select Start Subworkflow from the Select Next Node dropdown. Choose from workflows categorized as Local or Libraries.

2. Configure the Subworkflow Node

   • Workflow Selection: Pick the workflow to invoke.
   • Open: Edit the subworkflow in a new tab.
   • Preview: View the workflow canvas in a popup.
   • Response Key: Set a key (e.g., response_key) for output.
   • Input: Provide input in JSON format.
   • Output: Output is read-only JSON after execution.

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Data mapping

SaaS · 5.11

Available on SaaS with FlowX.AI 5.11. This feature is live on managed (SaaS) deployments now. Self-hosted deployments will receive it with the next LTS release family.

By default, a Subworkflow node forwards the whole parent context to the subworkflow and nests the result under the response key. Data mapping lets you instead pass only selected fields into the subworkflow and land its results directly into named parent variables, using visual input and output mappers rather than raw JSON.

In the node config panel, expand Data mapping and turn Enable data mapping on.

When data mapping is off, the node keeps its original behavior: the Input and read-only Output JSON fields described above. Turning Enable data mapping on replaces those with the mappers below.

When data mapping is on, the node exposes two mappers, driven by the subworkflow’s own start and end nodes:

Mapper	Helper text	Defined per	How it is labeled
Input mapping	Variables sent by the main workflow	The subworkflow start node	A single row labeled Start
Output mapping	Variables received by the main workflow	Each subworkflow end node	One row per end node, labeled with the end node’s name

Output mapping applies only to synchronous subworkflows. If the subworkflow runs asynchronously, the parent does not wait for a result, so the Output mapping block is hidden.

Each row opens a mapper modal. Use it to draw field-to-field mappings between the data models, then check the result before saving.

1. Open the mapper

   Click the edit icon on the Start row (input) or on an end-node row (output).

2. Map fields between the two data models

   The modal shows the source data model on the left and the target data model in the middle. Each side is color-coded: Project Data Model and Workflow Data Model. Draw the field-to-field mappings, or define static values and expression scripts where a direct field match does not exist.

3. Test the mapping

   Click Test to run the current mappings and preview the produced payload in the read-only results panel on the right. Any mapping errors are highlighted so you can correct them before saving.

4. Apply values from a past run (optional)

   To test against real data, pick a previous workflow instance from Past Instances Variables and click Apply to load that instance’s values as the source example. Use the reset control to return to the default example values.

5. Save

   Click Save to store the mapping on the node. In committed or upper environments the modal is read-only and shows Close instead.

Data mapping keeps the subworkflow’s contract explicit: the parent passes exactly the fields the subworkflow needs, and only the mapped results flow back. This is easier to maintain than forwarding the entire context and reading everything back through the response key.

Import, export, and clone

Subworkflow mappings are stored as part of the workflow definition, so they travel with the node when the workflow is exported, imported, or cloned.

On upgrade, existing Subworkflow nodes keep data mapping turned off, so they continue to behave exactly as before. Turn Enable data mapping on per node to adopt the mappers.

Use subworkflows for reusable logic such as data enrichment, validation, or external system calls.

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Parallel multi-instance

SaaS · 5.12

Available on SaaS with FlowX.AI 5.12. This feature is live on managed (SaaS) deployments now. Self-hosted deployments will receive it with the next LTS release family.

A Subworkflow node normally runs the child workflow once. Turn on Parallel Multi-Instance to run it once for every element of an array instead, in parallel, and collect the results back into a second array.

This keeps fan-out inside the Integration Designer. Previously, running a workflow once per item meant wrapping it in a process and fanning out with a multi-instance Call Activity.

In the node config panel, expand Execution and turn Parallel Multi-Instance on.

Turning Parallel Multi-Instance on also turns Enable Data Mapping on and locks it there, because each array element has to be mapped into the child workflow individually. The data mapping mappers stay available and work the same way.

Then set the two arrays:

Setting	Where	Required	What it does
Input Array	Input Mapping	Yes	The array of objects to iterate. One subworkflow instance starts per element.
Output Array	Output Mapping	Yes	The array each instance’s result is collected into.
Correlation attribute	Output Mapping	No	Decides which output array element each result updates.

Only array attributes from the workflow data model can be selected, and both arrays must be arrays of objects. If a dropdown offers nothing, the workflow data model has no array attributes to choose from.

How results land

The correlation attribute behaves as an upsert key rather than a strict join:

• A result whose correlation value matches an existing element of the output array updates that element.
• A result that matches no element is appended.
• With no correlation attribute set, every result is appended.

Correlation candidates are the primitive fields of the output array’s element, so pick the output array first. Until you do, the Correlation attribute selector stays empty.

If the merge fails, the still-running instances are cancelled and the output array is emptied. See Routing a subworkflow failure.

Point the input and output arrays at different data model attributes. Reusing one array as both the source and the target makes the upsert behavior hard to reason about.

Each instance runs the same subworkflow against one element, so if you need per-element branching, put it inside the child workflow rather than around the Subworkflow node.

Parallel multi-instance is not the same as parallel branches. Start Parallel and End Parallel nodes run several different branches of one workflow at the same time. Parallel multi-instance runs one subworkflow many times, once per element of an array. Use parallel branches for different work in parallel, and multi-instance for the same work over a collection.

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Execution logic and error handling

• Parent workflow waits for subworkflow completion before proceeding.
• If the subworkflow fails, the parent workflow halts at this node. On SaaS (5.12), connecting the node’s failure exit routes the failure down its own branch instead. See Routing a subworkflow failure.
• Subworkflow output is available to downstream nodes via the response key.
• Logs include workflow name, instance ID, and node statuses for both parent and subworkflow.

If a subworkflow is deleted, an error displays: [name] subworkflow not found.

Subworkflow runs are recorded in workflow instance history for traceability.

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Routing a subworkflow failure

SaaS · 5.12

Available on SaaS with FlowX.AI 5.12. This feature is live on managed (SaaS) deployments now. Self-hosted deployments will receive it with the next LTS release family.

A Subworkflow node has two exits, drawn as a green connector for success and a red one for failure. Connect the red exit to send a failed run down its own branch instead of stopping the parent workflow.

This is opt-in per node. A node whose red exit is not connected fails and blocks exactly as it did before, and nothing is changed for existing workflows.

Only a mapping failure is routed, because that is the kind of failure a workflow can be built to handle: the same workflow succeeds for records that carry the right fields.

Routed down the failure exit	Still stops the workflow
The input mapper fails	No subworkflow is set on the node
The input it produced does not satisfy what the subworkflow expects	The response key is missing
The output mapper fails when merging the result back	The node has no mapping configured at all
	The run hits the maximum node or subworkflow-depth limit

On the failure branch, the node writes a fixed subWorkflowError key, separate from its response key:

Field	Description
hasError	Always true. It exists so a branch reads the same shape here as on other node types.
errorMessage	For example, The input of subworkflow node [name] could not be mapped, so no subworkflow was started.
errorType	INPUT_MAPPING or OUTPUT_MAPPING, so a branch can tell a child that never started from one that ran and could not be merged back.
childInstanceUuid	The run whose result could not be mapped back. Left out entirely when no child was started.

The failure exit covers the node’s own mapping. A subworkflow that fails inside itself still cascades to the parent, whether or not the failure exit is connected.

A manual single-node run also reports the error to you rather than following the branch.

On a parallel multi-instance node, a merge failure cancels the sibling instances that are still running and empties the output array before taking the failure branch, so the branch never reads a half-filled list.

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Console logging, navigation, and read-only mode

• Console shows input/output, workflow name, and instance ID for each subworkflow run.
• Open subworkflow in a new tab for debugging from the console.
• Breadcrumbs enable navigation between parent and subworkflow details.
• In committed/upper environments, subworkflow configuration is read-only and node runs are disabled (preview/open only).

Subworkflow instances are logged in history, and you can navigate between parent and child workflow runs for comprehensive debugging.

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Use case: CRM Data Retrieval with subworkflows

Suppose you need to retrieve CRM details in a subworkflow and use the output for further actions in the parent workflow.

1. Create the Subworkflow

   Design a workflow that connects to your CRM system, fetches user details, and outputs the data in a structured JSON format.

2. Add a Subworkflow Node in the Parent Workflow

   In your main workflow, add a Subworkflow Node and select the CRM retrieval workflow. Map any required input parameters.

3. Use Subworkflow Output in Parent Workflow

   Downstream nodes in the parent workflow can reference the subworkflow’s output using the defined responseKey.

   {
     "crmData": "${responseKey}"
   }
   
4. Monitor and Debug

   Use the console to view input/output data, workflow names, and instance IDs. Open subworkflow runs in new tabs for detailed debugging.

This modular approach allows you to build scalable, maintainable integrations by composing workflows from reusable building blocks.

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End node

The End node signifies the termination of a workflow’s execution. It collects the final output and completes the workflow process.

• Receives input in JSON format from the previous node.
• Output represents the final data model of the workflow.
• Multiple End nodes are allowed for different execution paths.

If the node’s output doesn’t meet mandatory requirements, it will be flagged as an error to ensure all necessary data is included. Output parameters declared in the workflow’s output schema are a runtime contract: when any of them resolves to no value, the run fails with The mandatory output parameters of the <workflow> workflow are missing at runtime - see the error glossary.

A placeholder that doesn’t resolve fails silently on an End node: the output field is set to null, and the only error you see is the mandatory-output failure above. When mapping an End node output:

• Use the bare key with no prefix: ${responseKey.data}, not ${output.value} or ${input.responseKey.data}.
• Check the spelling against the Response Key configured on the REST node - the response body lives under <responseKey>.data.
• Leave the placeholder unquoted for numeric or boolean values; quote it ("${key}") only for strings.

To confirm what an End node actually produced, open the node in the workflow run details: it shows the exact input it received and the output JSON it emitted.