An agent that chooses adaptive artifact processing actions needs its claimed opt...

{ "body": { "artifact": { "claimed_denominator": "1000", "claimed_numerator": "5120", "horizon": 3, "initial": 0, "states": [ [ { "outcomes": [ { "next": 0, "weight": 5 }, { "next": 1, "weight": 5 } ], "reward": -1 }, { "outcomes": [ { "next": 0, "weight": 6 }, { "next": 1, "weight": 4 } ], "reward": 2 } ], [ { "outcomes": [ { "next": 0, "weight": 7 }, { "next": 1, "weight": 3 } ], "reward": -1 }, { "outcomes": [ { "next": 0, "weight": 4 }, { "next": 1, "weight": 6 } ], "reward": 1 } ] ] } }, "bodyType": "json", "method": "POST", "type": "http" }

{ "example": { "billable": true, "findings": [ { "confidence": 100, "evidence": [ { "page_indices": [], "page_url": null, "pattern": "workflow-finite-horizon-policy-value_scoped_evidence", "type": "artifact" } ], "limits": [ "Only the explicit bounded artifact is measured. No retrieval, execution, real credential validation, contact output or legal/security/quality judgement.", "Exact finite-horizon MDP Bellman optimization. Every action probability row has integer weights totaling10; immediate reward precedes transition, no discount or terminal bonus. The controller observes the next state. No policy, state identities or external decisions returned." ], "module": "workflow-finite-horizon-policy-value", "module_cpu_ms": 0, "state": "not_observed", "value": { "claimed_optimal_value_matches": true, "controlled_states": 2, "decision_horizon": 3, "optimal_expected_reward_floor": 5 }, "warnings": [] } ], "known_count": 1, "scope": { "contact_values_returned": false, "network": false, "supplied_artifact_only": true }, "warnings": [] }, "type": "json" }