Authentication
TypeSafe runs on Cargo credits by default, so you can use it without an account of your own. To bill TypeSafe directly instead, turn off Credits managed by Cargo on the connector and paste an API key created at console.typesafe.ai under Settings → Keys.Connection details
Credits
TypeSafe charges for the tokens it reads, not the ones it writes, so the cost follows the
size of your state and questions — the answers are free. Each call rounds up to the
next 1,000 tokens, so a short record costs 0.01 credits however many questions you ask it.
Batching questions into one node is therefore cheaper as well as faster: the state is
charged once instead of once per node.
The exact token count is in the action’s
usage.input_tokens output.
TypeSafe actions
Evaluate
Ask one or more typed questions about a state. Configuration
State takes plain text or structured data. Passing a record gives Jev the field names
as context, so
{"employees": 420, "industry": "robotics"} reads better than the same
values flattened into a sentence.
Each question has a Key — where its answer lands in the output, such as isIcp. The
key is not sent to the model, so name it for your workflow rather than for the question.
The three question types
Yes/no
Returns
noul, the probability that the answer is yes. There is no separate confidence
field, because the probability already carries it — 0.5 is the model telling you it
cannot decide.
Choice
Returns the winning option in
choice, every option’s probability in probabilities, and
a confidence derived from that distribution. Leave an option’s description empty when the
name says enough.
Score
Returns a probability-weighted
score that can land between levels — a 1.6 across
["Calm", "Frustrated", "Very angry"] sits between frustrated and very angry — plus the
legend mapping each level index back to its description.
Output
The node declares its output from the questions you wrote, so downstream nodes pick
answers.isUrgent.noul or answers.department.choice from the field list instead of
reaching into an untyped blob.
Use cases
Inbound routing
Inbound routing
One Choice question sends each inbound message to the team that should own it, and its
confidence decides whether to route automatically or send it to a human.
ICP qualification
ICP qualification
Score an account on fit, intent and timing as three separate questions, then weight
them in your own formula rather than in a prompt.
Guardrails
Guardrails
Screen generated copy before it sends, scoring how far off-brand or risky it is.
Best practices
- Ask one thing per question — a judgement that weighs several independent factors should be several questions combined in your own logic, not one question that has to reason
- Ask everything in one node — questions are evaluated in parallel and in isolation, so batching them is cheaper and faster than one node per question, and adding a question does not degrade the others. Splitting them across nodes pays for the state again each time
- Put the rules in
criteria, not the instructions — the option and level descriptions are where your domain’s boundary cases belong - Branch on
confidence, not just the answer — a low-confidence choice is the model telling you the case is genuinely ambiguous and worth a human - Give the state real structure — a JSON object with named fields beats a flattened string