n8n-nodes-decisions

An n8n community node for working with Decisions-compatible APIs.

It lets your n8n workflows evaluate content using AI models and receive structured answers with probabilities, making it possible to build reliable decision-making and routing workflows.

Supported APIs

• TypeSafe AI — System One models
• OpenRouter — access compatible models through OpenRouter
• OpenAI — OpenAI's Decisions API (beta)

Operations

The node provides two operations:

• Evaluate — evaluates each input item against one or more typed questions and adds the answers to the item.
• Route — evaluates a question and routes each item to an output based on the resulting answer.

You provide the model with a state (the content you want it to evaluate) and a set of typed questions describing what you want to know. The model returns a structured answer for each question, including probabilities.

This makes the node useful for tasks such as classification, content evaluation, decision-making, filtering, and conditional workflow routing.

Installation

Follow the installation guide in the n8n community nodes documentation, and use the package name n8n-nodes-decisions.

Credentials

Add a Decisions API credential and pick a Provider:

Provider	API Key	Base URL
TypeSafe AI	Create one in the TypeSafe console	Built in (https://api.typesafe.ai)
OpenRouter	Create one in your OpenRouter dashboard	Built in (https://openrouter.ai)
OpenAI	Create one in the OpenAI dashboard	Built in (https://api.openai.com)
Custom (Decisions Compatible)	Your provider key	Enter the provider base URL, e.g. https://api.custom.com/v1

Endpoint Path is optional. Leave it blank to use the default for your provider: /v1/systemone for TypeSafe AI and custom providers, /api/alpha/decisions for OpenRouter, /v1/decisions for OpenAI. Set a custom path only if your provider documents a different one. A custom provider speaking OpenAI's format should set API Style to OpenAI Decisions, which also switches its default path to /v1/decisions.

n8n checks the key when you save the credential.

Operations

Both operations send one request per input item. Each request includes the item's state, the Model ID, and the questions.

Model is a plain text model ID, e.g. jev-latest. The Models page describes TypeSafe models and their aliases. For OpenRouter or custom providers, enter the model ID your provider expects. Any OpenRouter model with the decisions output modality should work, e.g. typesafe/jev-latest; see the Decisions models on OpenRouter. For OpenAI, use gpt-6-luna; see OpenAI's Decisions guide.

State Format sets where the state comes from:

State Format	State sent
Text	The State field, as plain text
JSON	The State field, parsed as a JSON object or array
Input Item	The incoming item's JSON

All the questions in a request are asked about the same state. The State page covers how to structure it.

Evaluate

Evaluate asks one or more questions about the state and adds all the answers to the item. Each question is one of three question types:

Question Type	Answer
Choice	The option the model picked from your list, and its confidence
Score	A position along your levels, and its confidence
Noul (Yes/No)	The probability that the answer is yes, from 0 to 1

You can build the questions with the node's fields. Or you can set Questions Format to Using Raw JSON and pass in a JSON object of questions in the API's format, such as one built by an earlier node. The API reference documents that format.

Each answer goes in answers, under its question's ID:

{
  "answers": {
    "is_urgent":   { "noul": 0.95 },
    "department":  { "choice": "billing", "confidence": 0.81 },
    "frustration": { "score": 1.05, "confidence": 0.92 }
  },
  "model": "jev-1.13.0"
}

When an AI Agent uses the node as a tool, the node runs Evaluate.

With OpenAI, Noul questions are sent as predicate questions and their answer is probability instead of noul. A question the model declines comes back as { "type": "refusal" }. Raw JSON can also be an array of questions in OpenAI's format.

Low confidence handling

Evaluate can flag answers the model is unsure about. Set Fallback Mode to choose how, and Confidence Threshold (0–1, default 0.7) to set when an answer counts as low confidence: an answer with confidence strictly below the threshold is low confidence. It works the same for questions built in the UI and for Raw JSON, because it runs on the API response. The raw noul, choice, score and probability values are never modified.

Confidence is normalized to 0–1. Choice and Score use the confidence the API returns. Yes/No questions have no confidence field, so it is derived as |p − 0.5| × 2, so 0.85 → 0.70. A refusal always counts as low confidence. A Choice or Score answer without a confidence value is treated as reliable. The threshold must be a finite number in 0–1; anything else is an error.

Fallback Mode	Behaviour
Disabled (default)	Today's output, unchanged. No fields are added.
Best Guess	One output. Every answer gains lowConfidence, plus confidence where the answer has a confidence source (derived for Yes/No, 0 for a refusal). Yes/No answers also gain value, resolved as p > 0.5. Exactly 0.5 resolves to false: with no evidence for yes, the node does not assert it. Choice and Score never gain value.
Low Confidence Output	Two outputs: Confident and Low Confidence. Every answer gains lowConfidence, plus confidence where the answer has a confidence source, and the item gains lowConfidence plus lowConfidenceQuestions (the IDs of the doubtful questions). If any question is low confidence, the whole item goes to Low Confidence. No value is resolved. A refusal always goes to Low Confidence.

Fallback Mode is not settable by expression. Chaining two Decisions nodes recomputes these fields, overwriting the previous node's confidence, lowConfidence, lowConfidenceQuestions and value. When an AI Agent uses the node as a tool, prefer Disabled or Best Guess so the agent receives a single result. Answers without a confidence source (for example a Score without confidence) are treated as reliable and gain no confidence field.

Best Guess output:

{
  "answers": {
    "is_urgent": { "noul": 0.55, "confidence": 0.1, "lowConfidence": true, "value": true },
    "department": { "choice": "billing", "confidence": 0.81, "lowConfidence": false }
  },
  "model": "jev-1.13.0"
}

Low Confidence Output, on the Low Confidence output:

{
  "answers": {
    "is_urgent": { "noul": 0.55, "confidence": 0.1, "lowConfidence": true },
    "department": { "choice": "billing", "confidence": 0.81, "lowConfidence": false }
  },
  "model": "jev-1.13.0",
  "lowConfidence": true,
  "lowConfidenceQuestions": ["is_urgent"]
}

Route

Route asks one question and sends the item to the output that matches the answer. Question Type sets the kind of question and the outputs you get:

Question Type	Outputs	An item goes to
Choice	One per route, labelled with its Name	The route the model picked
Noul (Yes/No)	True and False, labelled with True Means and False Means if you fill them in	True if p > 0.5, False otherwise — or to Low Confidence when unsure, see below
Score	One per level, labelled with the level's text	The level nearest the score

All three question types share one confidence model. Yes/No confidence is |p − 0.5| × 2, so a threshold c means p ≥ 0.5 + c/2 (true) or p ≤ 0.5 − c/2 (false). Set Confidence Handling to Route to Separate Low Confidence Output to add an extra output for unsure items (Low Confidence in version 2; Fallback for Choice in version 1). An item goes there when its answer's confidence is below Confidence Threshold (default 0.7 for all question types since version 2 — previously 0.5 for Choice routes). A Choice or Score answer without a confidence value is treated as reliable and follows its route or level.

• Choice: Fallback output. Set Confidence Handling to Route to Separate Low Confidence Output to add a Low Confidence output (Fallback in version 1). An item goes there when its answer's confidence is below Confidence Threshold.
• Noul: Low Confidence output. With a separate output enabled, an unsure item goes to Low Confidence. Without it, the item follows p > 0.5.
• Score: level boundaries. Levels are numbered from 0, lowest first. The boundary between two levels is halfway between their numbers. A score from 0.5 to just under 1.5 goes to level 1, and a score exactly on a boundary goes to the higher level. With a separate output enabled, a low-confidence item goes to Low Confidence instead of its level.

Workflows saved with node version 1 keep the old Noul behaviour: True/False Probability Thresholds with an Uncertain output for the gap between them. Those thresholds are not offered in version 2, and an asymmetric v1 gap cannot be expressed as a single confidence threshold.

The route field holds the answer in the same form Evaluate uses, and the output the item leaves from shows the decision. If the model refuses the route question, that is a failure, handled as in Errors below — it never routes to a decision output.

{ "route": { "choice": "billing", "confidence": 0.81 }, "model": "jev-1.13.0" }

Example workflow

This workflow triages support tickets. A webhook receives each ticket, and the Decisions node's Route operation asks a Choice question with three routes: billing, tech support and sales. Each route's output leads to that team. Confidence Handling is set to Route to Separate Fallback Output, so a ticket answered below Confidence Threshold leaves from Fallback instead. A Switch node then sends it on by its confidence, either to be flagged for review or to a human queue.

Output

The node writes these fields to each item:

Field	Contents
answers	Evaluate: all the answers, keyed by question ID
route	Route: the answer to the route question
model	The full ID of the model that answered, including its version, such as jev-1.13.0
usage	Token usage, when Simplify is off

Three settings under Options change how the node calls the API and what it writes:

• Simplify is on by default. It keeps each answer's noul, choice or score, plus confidence for question types that return it, under the API's field names. When it's off, each answer is the full answer object from the API, including probabilities, and the item also gets usage.
• Include Other Input Fields is on by default. It keeps the incoming item's fields and binary data, then writes the node's fields on top, replacing any incoming field with the same name. When it's off, the item has only the node's fields.
• Timeout is how long, in milliseconds, the node waits for the API to start responding. The default is 5000 and the minimum is 1000.

Errors

When something goes wrong, the node stops and shows an error. A failed request shows the HTTP status and the API's error message. A setup problem, such as empty Instructions or a duplicate route name, shows a message saying what to fix.

In the node's Settings, turn on Retry On Fail to retry failed requests, including rate-limit errors (429).

To keep the workflow running when an item fails, set On Error:

• Continue (using error output) adds an error output to the node and sends each failed item there, with an error field.
• Continue sends each failed item, with an error field, to one of the node's regular outputs:

Operation	Output the failed item goes to
Evaluate	The main output, or Low Confidence when Low Confidence Output is on
Route, Choice	Low Confidence (Fallback in version 1) if enabled, otherwise the first route
Route, Noul (Yes/No)	Low Confidence if there is one, otherwise False (Uncertain if there is one, otherwise False, in version 1)
Route, Score	Low Confidence if there is one, otherwise the first level

Compatibility

Tested with n8n 2.40.

This package is a fork of typesafe-ai/n8n-nodes-typesafe-ai, renamed to n8n-nodes-decisions with the node decisions and the credential decisionsApi. It is not a drop-in upgrade: workflows built with the TypeSafe AI node need the node and credential replaced.

Resources

• TypeSafe AI quickstart
• TypeSafe AI documentation
• TypeSafe AI API reference
• OpenRouter documentation
• OpenAI Decisions guide
• n8n community nodes documentation

Version history

See CHANGELOG.md.