Direct answer
An AI app action schema describes what an assistant may suggest or start inside an app. A useful schema names the intent, required inputs, destination, confirmation requirement, authentication level, allowed outcome, and proof of completion.
Where this applies
- A commerce app needs a buy flow that distinguishes cart creation from payment submission.
- A travel or appointment app needs reservation actions with date, location, and cancellation details.
- A SaaS app needs contact, invite, export, and save actions with clear role permissions.
- A backend team needs API contracts that match app screens and user-facing copy.
Operating steps
- Start with the user job and choose a plain-language action name.
- Define required inputs, optional inputs, default values, and invalid states.
- Choose the deep link, API, or web route that starts the task safely.
- Add confirmation, step-up auth, and no-auto-execute rules for sensitive outcomes.
- Test the schema against real tasks and update copy when users misunderstand an action.
Common risks
- Overbroad actions can let an assistant do more than the user intended.
- Unclear required inputs can create failed or partial tasks.
- Backend APIs may allow actions the UI would normally block or confirm.
- Missing completion evidence makes it hard to trust whether the task actually finished.