A Choice picks one option from a set you define and returns a probability for every option. Here is how to read the distribution and its confidence, why a none-of-the-above option matters, how contrastive descriptions sharpen close calls, and what reversing the option order did to 3,080 real answers.
Key takeaways
- A Choice returns the chosen option, a probability for every option, and a confidence that summarizes how peaked that distribution is.
- A split distribution is information: a ticket that belongs to two teams should look split.
- Always offer a none-of-the-above option when inputs can fall outside your list; otherwise the model must pick something.
- Option names and descriptions are both sent to the model; for close calls, describe what each option covers and what it doesn't.
- Option order can sway uncertain answers: in our test, reversing 77 options changed 4.9% of answers, none above 0.9 probability.
Try it with your agent
Paste this into your coding agent:
Review every multiple-choice decision we ask a model to make. For each: 1. Is the option list complete? Add an explicit "other" / none option if inputs can fall outside it. 2. Does each option have a one-line description? For options that are often confused, add contrastive what / not_for / examples fields. 3. Does code treat low-confidence answers differently? 4. Add a test that re-asks 20 known close calls with the options shuffled and reports any answer that changes.
Transcript
Intro
Most decisions in software pick one thing from a list: which team, which category, which intent. That's a Choice. Let's see what it gives back, and the four habits that make it reliable.
Reading a Choice
Here's a messy ticket. Shoes arrived late and in the wrong size, and there are two charges on the card. Which team should handle it? Returns wins at point six three, but billing gets point three three, because of the double charge. That split is honest. This ticket belongs to two teams.
Confidence turns that shape into one number. Zero means the probability is spread evenly. One means it's all on one option. Here it's point four five. It's computed from the probabilities, so you can always check it, or use your own measure, like the gap between the top two options.
None of the above
Habit one: always offer a way out. Someone writes in to apply for a designer job. Your options are returns, shipping and billing. Without an other option, the model has to pick something: billing, at point five, spread thin. Add other, described as none of the above, and it goes there with all the probability.
Describe the options
Habit two: describe the options. The model reads both the option names and their descriptions. For options that get confused, say what each one covers, what it's not for, and give an example or two. On a borderline question about where a disposable card works, plain names gave point nine. Contrastive descriptions gave a clean one point oh.
In code, it looks like this. Each option gets the same fields, so the model can compare them side by side. You only need this for the pairs that actually get confused. Clear options can keep a one line description, or none at all.
Give the full list
Habit three: give the full list. Jev accepts up to two hundred fifty five options, and each one costs only a few tokens. Don't hand-pick a shortlist; offer every team, every category. For deep taxonomies with thousands of leaves, go level by level, which we'll cover in the composition module.
Option order
Habit four: watch the order. TypeSafe's docs warn that Jev can lean toward the first option. So we reversed the order of all seventy seven intents and reran 3,080 messages. Four point nine percent of answers changed. But look where: thirty six percent of answers under point five flipped, and not a single answer above point nine.
That's the pattern you'll see all through this course. When the model is sure, small changes don't move it. When it isn't, they do, and the probability tells you which case you're in. So route low confidence answers to review, and for close calls you care about, ask again with the options shuffled.
Quick check
Quick check. A support bot classifies messages into five departments. A message arrives about something none of them handle. What happens if the Choice has no other option?
Try it
Try it. Have your agent audit every Choice in your code for the four habits.
Recap
So: a Choice gives you a distribution, and its confidence says how peaked it is. Offer a way out. Describe the options that get confused. Give the full list. And remember that low confidence answers are the fragile ones. Next: the Score.