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GET
/
api
/
strategies
/
agent
/
{agent_id}
Get agent strategies
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>"
}

Documentation Index

Fetch the complete documentation index at: https://docs.minns.ai/llms.txt

Use this file to discover all available pages before exploring further.

​
Path parameters

​
agent_id
integer
required
Agent identifier (u64).

​
Query parameters

​
limit
integer
default:"10"
Maximum number of strategies to return. Max: 1000.

​
Response

Returns an array of StrategyResponse objects.
​
id
integer
Strategy identifier.
​
name
string
Strategy name.
​
agent_id
integer
Agent that learned this strategy.
​
quality_score
number
Quality score (0.0–1.0).
​
success_count
integer
Number of successes.
​
failure_count
integer
Number of failures.
​
reasoning_steps
ReasoningStepResponse[]
Ordered steps in the strategy.
​
strategy_type
string
Strategy classification.
​
support_count
integer
Number of supporting episodes.
​
expected_success
number
Expected success rate (0.0–1.0).
​
expected_cost
number
Expected cost.
​
expected_value
number
Expected value.
​
confidence
number
Confidence in strategy (0.0–1.0).
​
goal_bucket_id
integer
Associated goal bucket.
​
behavior_signature
string
Unique behavior signature.
​
precondition
string
When to apply this strategy.
​
action_hint
string
Suggested action.

​
ReasoningStepResponse

FieldTypeDescription
descriptionStringStep description
sequence_orderusizeOrder in the sequence
[
  {
    "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"
  }
]