925fff731f
- Memorizer tracks user_expectation (conversational/delegated/waiting_input/observing) - Output node adjusts phrasing per expectation - PA retry loop: reformulates job on expert failure (all retries exhausted or tool skip) - Machine state in PA context: get_machine_summary includes current state, buttons, stored data - Expert writes to machine state via update_machine + transition_machine - Expanded baked schema coverage - Awareness panel shows color-coded expectation state - Dashboard and workspace component updates Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
1.3 KiB
1.3 KiB
Machine State → PA Context
Tests that PA reads machine state when routing, and experts can write back to machines. Validates: enriched machine summary, update_machine, transition_machine.
Setup
- clear history
Steps
1. Create a machine
- send: create a navigation machine called "wizard" with initial state "start" and a second state called "details"
- expect_trace: has machine_created
2. PA sees machine in context
- send: what machines are active on my dashboard?
- expect_response: contains "wizard" or "start"
3. Expert stores data on machine
- send: use update_machine to store region=Bayern on the wizard machine
- expect_response: contains "Bayern" or "region" or "stored" or "updated"
4. PA sees stored data
- send: what data is stored in my wizard machine?
- expect_response: contains "Bayern" or "region"
5. Expert transitions machine to details
- send: use transition_machine to move wizard to details state
- expect_response: length > 5
6. PA sees updated state
- send: what state is the wizard in now?
- expect_response: contains "details"
7. Expert transitions back
- send: use transition_machine to move wizard back to start
- expect_response: length > 5
8. Final state check
- send: tell me the current wizard state and stored data
- expect_response: contains "start"