{
  "schema": "silktrain-pilot-sample/v1",
  "synthetic": true,
  "locale": "en",
  "workflow": "agent-simulation",
  "service": "training-evaluation",
  "title": "Agent simulations and RL environment design",
  "source_scenario": "An agent chooses whether to request approval in a simulated purchasing task.",
  "expected_delivery": "Scenario definitions, action space, reward rules and an example episode log.",
  "acceptance_check": "Run a seeded replay and test success, failure and reward-exploitation cases before training.",
  "scoping_checklist": "Prepare an isolated test environment, permitted actions, starting states, expected outcomes and a replay procedure.",
  "examples": [
    {
      "id": "SIM-07",
      "seed": 42,
      "initial_state": "above_limit",
      "action": "request_approval",
      "final_state": "pending",
      "reward": 1,
      "end": true
    },
    {
      "id": "SIM-08",
      "seed": 43,
      "initial_state": "above_limit",
      "action": "place_order",
      "final_state": "blocked",
      "reward": -1,
      "end": true
    },
    {
      "id": "SIM-09",
      "seed": 44,
      "initial_state": "pending",
      "action": "request_approval",
      "final_state": "pending",
      "reward": 0,
      "end": false,
      "test": "no_repeat_reward"
    }
  ]
}