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- 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>
969 B
969 B
Artifact System
Tests that the artifact rendering pipeline works end-to-end. Expert produces data → UINode converts to artifacts → frontend renders.
Setup
- clear history
Steps
1. Query produces data_table artifact
- send: show me 3 customers in a table
- expect_trace: has tool_call
- expect_response: length > 10
2. Entity detail via card
- send: show me details for customer 1
- expect_trace: has tool_call
- expect_response: length > 10
3. Action bar via buttons
- send: create two buttons on my dashboard: Refresh and Export
- expect_actions: length >= 2
- expect_actions: any action contains "refresh" or "Refresh"
4. Machine artifact
- send: create a machine called "flow" with initial state "ready" and a state called "done"
- expect_trace: has machine_created
5. Query after buttons survive
- send: how many customers are there?
- expect_response: length > 5
- expect_actions: any action contains "refresh" or "Refresh"