edu-demo-orchestrator

Multi-agent educational demos are orchestrated by defining test cases for learning objectives, spawning diverse builder agents, running Chrome-based evaluations, and synthesizing lessons learned to guide iterative improvements. This ensures automated task planning and structured evaluation.

Evaluating learning outcomes in automated experiments requires defining test cases upfront, running Chrome-based end-to-end browser evaluations with real user-like interactions, and aggregating results to measure if educational objectives were met.

Multi-agent orchestration applies to educational content generation by spawning diverse agents to explore narrative, comparison, hands-on, and hybrid teaching approaches, generating varied demo strategies from a single problem definition.

Defining test cases before building educational demos is required. This test-case-first workflow establishes clear learning objectives upfront, ensuring subsequent builder agents generate content that can be accurately evaluated against structured criteria.

Automated e2e testing for educational scenarios is conducted using Chrome-based browser evaluations. This process simulates real user-like interactions to verify that generated educational demos function correctly and meet predefined learning goals.

A test-case-first workflow for multi-agent educational orchestration defines learning objectives via test cases before building demos. It ensures builders generate content aligned with measurable outcomes, followed by structured evaluation and documentation of lessons learned.