{
  "context": "This criteria evaluates how well the engineer uses the python-Levenshtein package's custom edit cost capabilities, specifically the insertion_cost, deletion_cost, and substitution_cost parameters of the distance function. The focus is entirely on proper usage of these package-specific features.",
  "type": "weighted_checklist",
  "checklist": [
    {
      "name": "Uses Levenshtein.distance",
      "description": "Implementation calls the Levenshtein.distance() function to compute edit distances rather than implementing a custom algorithm",
      "max_score": 30
    },
    {
      "name": "Passes insertion_cost parameter",
      "description": "Correctly passes the insertion_cost parameter to Levenshtein.distance() using the insertion_cost keyword argument",
      "max_score": 20
    },
    {
      "name": "Passes deletion_cost parameter",
      "description": "Correctly passes the deletion_cost parameter to Levenshtein.distance() using the deletion_cost keyword argument",
      "max_score": 20
    },
    {
      "name": "Passes substitution_cost parameter",
      "description": "Correctly passes the substitution_cost parameter to Levenshtein.distance() using the substitution_cost keyword argument",
      "max_score": 20
    },
    {
      "name": "Correct parameter mapping",
      "description": "Maps the function's custom cost parameters correctly to the Levenshtein.distance() function without swapping or misaligning parameters",
      "max_score": 10
    }
  ]
}