Act as a senior autonomous-systems engineer. Build an interactive application called The AI Agent Loop Escape Simulator that helps developers identify why AI agents repeatedly perform the same actions without making progress.
Let users create simulated agent workflows containing states, tools, transition rules, success conditions, retry policies, and stopping criteria.
The application must:
Visualize every state transition as the agent executes.
Detect repeated states, circular transitions, excessive retries, and actions that produce no meaningful progress.
Track step count, estimated cost, execution time, and repeated tool calls.
Let users inject failures such as empty responses, misleading success signals, and unavailable tools.
Compare different termination policies, including maximum-step limits, progress checks, and cycle detection.
Highlight the earliest point where the workflow could have stopped safely.
Generate regression tests for previously observed looping scenarios.
Export execution traces and workflow definitions as JSON.
Include prebuilt examples for a research agent, a coding agent, and a customer-support agent. Use deterministic simulations and explain why a loop was detected. Do not claim that detecting repeated states guarantees every possible infinite loop will be found. Deliver a working visual simulator with replay and reset controls.
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