The AI Agent Handoff Failure Simulator

 Create an interactive simulator for testing what happens when complex tasks pass between multiple AI agents.

Users define a workflow containing specialized agents, task descriptions, shared context, intermediate outputs, acceptance criteria, and dependencies.

The simulator should introduce configurable failure scenarios:

1. An agent omits a critical requirement from its handoff.

2. An agent interprets an ambiguous instruction differently from the previous agent.

3. Two agents produce conflicting outputs.

4. An agent repeats work already completed by another agent.

5. An intermediate result contains an unsupported claim.

6. A downstream agent proceeds despite missing required evidence.

7. A task is delegated without enough context or authority.

Track how each failure propagates through the workflow and identify the earliest point where a validation gate could have prevented it.

Provide a visual execution timeline, context-transfer inspector, failure injection controls, and side-by-side comparisons of alternative handoff protocols.

Support deterministic replay using fixed inputs and explicitly configured failure rules. Distinguish simulated agent behavior from measured model performance. Include configurable acceptance tests, structured handoff schemas, and downloadable execution traces.