Build the agent
Score a release against real cases
Turn the situations an agent must handle into tests, and let them stand between a draft and production.
Give each test checks that say what a good answer does, run the tests against your latest changes, and require a passing run before an agent publishes.
What this changes for your team.
A test is a situation the agent should handle: one you script, a real conversation you kept, or a live request. Checks say what a good answer to it does - the reply it gives, the tools it uses, the values it sends - and every run of your latest changes is judged against them, check by check. Where you want the tests to be binding, require passing tests to publish for that agent and a publish waits for a pass.
How it works in practice.
- 01
Write tests, ask Agent Builder to write them, or save a conversation worth keeping as one, then add checks on what a good answer does.
- 02
Run every test against your latest changes - more than once, to tell a reliable pass from a lucky one - and read each check's result.
- 03
Require passing tests to publish for the agents where a passing run should be a condition of publishing.
What you can plan around.
What to expect, including limits that matter to your team.
A check is tried when you write or edit it: against the recorded conversation on a test saved from one, so a check that could never pass is refused as a typo rather than failing at the next release.
A test with no checks reports as unscored - a third state everywhere it appears, and never counted as a pass.
The requirement matches the tested draft against the exact setup being published, using the same comparison that decides whether there are changes to publish at all.
A run's totals are counted from the tests inside it, so a headline result and its tests cannot drift apart.
Bring one real process
See how Yekar.AI fits the way you work.
Start with a job your team already owns, plus the tools and decisions around it.
Get started