Stop and Error

error-handling.stop-and-error Error Handling v0.1.0

Unconditionally fails the flow with a configured error code and message — catchable by an enclosing Try, otherwise it fails the run.

Finding it in the library

Search the builder's node library for Stop and Error (it lives under Error Handling). A single click opens the in-editor docs panel shown here — description, ports, and every property, without leaving the canvas. Double-click (or drag) to add it to the workflow.

Library capture pending — regenerate with npm run shots:nodes.

Wired up in the builder

Stop and Error in a real, runnable flow — captured live from the Studio editor, exactly as it looks on your canvas. This is the same workflow used for the example input & output below.

Canvas capture pending — regenerate with npm run shots:nodes.

How it’s configured

The node’s Configure panel as it opens in the builder when you select the step — every setting laid out with real values. Click any field to edit it.

Config capture pending — regenerate with npm run shots:nodes. See the full property reference below.

Ports

Ports are the node’s contract with its neighbours. In the editor a port label renders bold when wired and italic when optional; ports accept attachment carriers rather than data wires.

DirectionPortLabelWhat flows through it
InputinputInput

How data flows through it

Stop and Error consumes the content of the incoming envelope — when it is fed directly by a trigger, the trigger’s wrapper is unwrapped at the node boundary so the node sees the actual data, not the metadata shell. Its output becomes the payload for the next node, while the envelope (trace ids, correlation, binary refs) rides along untouched. In the Runs view you always see the whole envelope for both sides of this node.

Expressions in the config

String-typed properties accept {{ }} expressions evaluated against the incoming item at run time — e.g. {{ $json.customer.email }}. On this node that’s message, errorCode. JSON- and code-typed fields never interpolate — they are passed through literally.

Build it with AI

Every node in this reference is reachable through Flowdrome’s AI Copilot and the MCP tools — say what you want, and the graph surgery happens server-side. Node types resolve fuzzily, so the catalog label (Stop and Error) works as well as the exact type id (error-handling.stop-and-error).

In the Copilot panel (or any connected AI):

add a stop and error node after the trigger

As a step in a create_chain_workflow call:

{"type":"Stop and Error","config":{}}
Raw MCP call — add this node to a workflow with add_node
curl -s -X POST http://localhost:48170/mcp -H "content-type: application/json" -d '{ "jsonrpc": "2.0", "id": "1", "method": "tools/call", "params": { "name": "add_node", "arguments": { "workflowId": "<id>", "type": "Stop and Error" } } }'

Example input & output

Captured from a real test run of the workflow above — this is what you see in the run data panel after pressing Test workflow. This particular run fails by design (see the note below).

This run fails BY DESIGN — Stop and Error exists to raise a designed failure, so the example shows the raised error instead of an output.

Input — what the node received

{
  "kind": "json",
  "contentType": "application/json",
  "payload": {},
  "body": {}
}

Output — what the node produced

This step raised: smoke boom

Property reference

Every setting, with its type and default — the same fields shown configured in the panel above.

PropertyTypeDefaultDescription
Error message
message
string "" The failure message. Supports ${variable.NAME} / ${credential.NAME.FIELD} substitution at run start.
Error code
errorCode
string "STOPPED_BY_NODE" Machine-readable error code carried by the failure (and by error-handling.error's payload).

Related nodes

The rest of the Error Handling group — the same folder you’d scan in the editor’s library.

This page is generated from the node registry by gen-node-docs.mjs on every site build — ports, properties, defaults and visibility rules cannot drift from the code. The screenshots and example data are captured from a live Flowdrome by npm run shots:nodes and npm run gen:examples.