FIX: Update openenv.yaml to use graders module instead of task_graders - ensures validator can discover all 5 graders

graders.py

@@ -13,6 +13,15 @@ returning a score from 0.0 (worst) to 1.0 (best).
 
 from models import EnergyOptimizationObservation
 
+# Explicit exports for validator discovery
+__all__ = [
+    'grade_basic_ram_reduction',
+    'grade_energy_optimization',
+    'grade_balanced_optimization',
+    'grade_advanced_efficiency',
+    'grade_expert_optimization',
+]
+
 
 def grade_basic_ram_reduction(observation: EnergyOptimizationObservation) -> float:
     """Grade performance on basic RAM reduction task: Reduce RAM usage below 70%."""

openenv.yaml

@@ -8,26 +8,26 @@ port: 8000
 tasks:
   - name: basic_ram_reduction
     description: "Reduce RAM usage below 70% within 10 steps"
-    grader: task_graders:task_1_basic_ram_reduction_grader
+    grader: graders:grade_basic_ram_reduction
     max_steps: 10
 
   - name: energy_optimization
     description: "Reduce energy consumption below 6 kWh while keeping RAM below 75%"
-    grader: task_graders:task_2_energy_optimization_grader
+    grader: graders:grade_energy_optimization
     max_steps: 15
 
   - name: balanced_optimization
     description: "Balance RAM below 60% and energy below 5 kWh within 20 steps"
-    grader: task_graders:task_3_balanced_optimization_grader
+    grader: graders:grade_balanced_optimization
     max_steps: 20
 
   - name: advanced_efficiency
     description: "Achieve RAM below 50% and energy below 4 kWh within 25 steps"
-    grader: task_graders:task_4_advanced_efficiency_grader
+    grader: graders:grade_advanced_efficiency
     max_steps: 25
 
   - name: expert_optimization
     description: "Master level: RAM below 40% and energy below 3 kWh within 30 steps"
-    grader: task_graders:task_5_expert_optimization_grader
+    grader: graders:grade_expert_optimization
     max_steps: 30