> ## Documentation Index
> Fetch the complete documentation index at: https://developers.arg.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Jev

> Ask TypeSafe AI's Jev typed questions about your content and get calibrated, structured answers back.

Jev is TypeSafe AI's decision model. It writes no prose: you give it some content and a typed question, and it answers with a probability distribution, so the result is a value your workflow branches on rather than a sentence something has to parse. It connects with a TypeSafe API key.

## What you can do

**Actions** - pick one option from a set, rate against a rubric, answer a yes/no question as a probability, ask many questions about the same content in one call, and list the models your account can use.

**Triggers** - none. Use it through the assistant in chat or as an action node in an automation.

## Get your credential

<Steps>
  <Step title="Open the TypeSafe console">
    Sign in at [console.typesafe.ai](https://console.typesafe.ai) and go to **API keys**.
  </Step>

  <Step title="Create a key">
    Create a key and copy it. Usage bills to that TypeSafe account, charged per input token - answers cost nothing.
  </Step>
</Steps>

## Connect

<Steps>
  <Step title="Open Integrations">
    In arg.ai, go to **Settings → Integrations** and click **Connect** on **Jev**.
  </Step>

  <Step title="Paste the key">Enter your API key in the API key field.</Step>
  <Step title="Save">arg.ai checks the key against your TypeSafe model list and connects it.</Step>
</Steps>

## Use it

* **In chat:** *"Score each of these bug reports for severity with Jev and list the blocking ones."*
* **In an automation:** add a **Jev** action node to classify an incoming message, then branch on the option it picked.

## The three question types

* **Pick one option** takes a map of option name to what that option means, 2 to 255 of them. The answer names one of your options and carries a probability for every one of them.
* **Rate against a rubric** takes 2 to 10 level descriptions ordered low to high, indexed from 0. The score is probability-weighted, so it can land between levels - `1.4` means the content sits between your second and third level.
* **Answer yes or no** returns a single number from 0 to 1. Threshold it in your own code rather than treating `0.51` as a yes.

## Confidence, and asking more than one question

A pick-one and a rate answer each carry a `confidence` between 0 and 1, derived from how concentrated the probability is. Read it as a second axis: the answer says what, and the confidence says whether to act on it or hand the item to a person.

Jev reads the content once and answers every question against it in parallel, so **ask many questions at once** is markedly cheaper and faster than one call per question - which makes speculative questions you may not end up reading nearly free. Ask everything you might want in one call and decide in your own code which answers matter.

## Limits

One request covers 64k tokens of content plus all of its questions, and 32k for the content plus the single longest question. Input is text: a string, or a JSON object or array of text values. Pre-process images, audio, and binaries into text before sending them.