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tile.json

rubric.jsonevals/scenario-9/

{
  "context": "This criteria evaluates how well the engineer leverages Nx's intelligent task scheduling capabilities, specifically focusing on historical timing data for task prioritization and optimized execution order. The evaluation assesses the proper use of Nx's task orchestration, caching mechanisms, and execution APIs.",
  "type": "weighted_checklist",
  "checklist": [
    {
      "name": "Task Graph Construction",
      "description": "Uses Nx's task graph APIs (createProjectGraphAsync, TaskGraph, or ProjectGraph) to properly model task dependencies and build the execution graph structure.",
      "max_score": 20
    },
    {
      "name": "Historical Data Storage",
      "description": "Leverages Nx's caching system (NxCache, DbCache, or similar) or configuration storage mechanisms to persist and retrieve historical task execution timing data across runs.",
      "max_score": 20
    },
    {
      "name": "Task Prioritization Logic",
      "description": "Implements intelligent scheduling that uses historical timing data to prioritize tasks, ideally using Nx's TaskOrchestrator or task scheduling APIs that support priority-based execution ordering.",
      "max_score": 25
    },
    {
      "name": "Parallel Execution",
      "description": "Uses Nx's task execution capabilities (runExecutor, defaultTasksRunner, or similar) to execute independent tasks in parallel while respecting dependencies.",
      "max_score": 20
    },
    {
      "name": "Execution Recording",
      "description": "Properly records task execution results and timing using Nx's execution result interfaces (ExecutorContext, TaskResult, or similar) to update historical data after each run.",
      "max_score": 15
    }
  ]
}