cURL
curl --request GET \ --url https://api.example.com/api/strategies/agent/{agent_id}
{ "id": 123, "name": "<string>", "agent_id": 123, "quality_score": 123, "success_count": 123, "failure_count": 123, "reasoning_steps": [ {} ], "strategy_type": "<string>", "support_count": 123, "expected_success": 123, "expected_cost": 123, "expected_value": 123, "confidence": 123, "goal_bucket_id": 123, "behavior_signature": "<string>", "precondition": "<string>", "action_hint": "<string>" }
Retrieve learned behavioral strategies for a specific agent.
u64
1000
StrategyResponse
0.0
1.0
description
String
sequence_order
usize
[ { "id": 1, "name": "movie_booking_standard", "agent_id": 1, "quality_score": 0.92, "success_count": 15, "failure_count": 2, "reasoning_steps": [ { "description": "Greet user and confirm movie title", "sequence_order": 0 }, { "description": "Check seat availability", "sequence_order": 1 }, { "description": "Process booking", "sequence_order": 2 } ], "strategy_type": "sequential", "support_count": 17, "expected_success": 0.88, "expected_cost": 0.15, "expected_value": 0.85, "confidence": 0.91, "goal_bucket_id": 101, "behavior_signature": "greet→check→book", "precondition": "User requests movie booking", "action_hint": "Start with greeting and title confirmation" } ]