fix: reject broken configs and improve accuracy feedback with isolated agent state

modelhub_submmit_api/outcome_tracker.py

@@ -22,6 +22,8 @@ from history_stats import classify_failure, is_failure, is_success
 from llm_classifier import LLMAssistedClassifier
 from modelhub_client import ModelHubClient, ModelHubClientPool
 from task_registry import task_type_from_history_task
+from common import runtime_instance_id
+from version import AGENT_VERSION
 
 
 DEFAULT_OUTCOMES_PATH = Path("outcomes/submissions.jsonl")
@@ -36,6 +38,7 @@ FAILURE_ENRICHMENT_MAX_ATTEMPTS = 3
 TERMINAL_TASK_STATUSES = {"success", "failed", "error", "cancelled", "completed"}
 
 DECISION_RECORD_FIELDS = {
+    "agentVersion", "instanceId", "strategyId",
     "taskId",
     "modelId",
     "targetGpu",
@@ -325,6 +328,9 @@ class OutcomeTracker:
         model_profile: dict[str, Any] | None = None,
     ) -> None:
         record: dict[str, Any] = {
+            "agentVersion": AGENT_VERSION,
+            "instanceId": runtime_instance_id(),
+            "strategyId": os.getenv("STRATEGY_ID"),
             "modelId": model_id,
             "targetGpu": target_gpu,
             "framework": framework,