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pypipkg:pypi/python-levenshtein@0.27.x
tile.json

tessl/pypi-python-levenshtein

tessl install tessl/pypi-python-levenshtein@0.27.0

Python compatibility wrapper for computing string edit distances and similarities using fast Levenshtein algorithms.

Agent Success

Agent success rate when using this tile

88%

Improvement

Agent success rate improvement when using this tile compared to baseline

1.38x

Baseline

Agent success rate without this tile

64%

rubric.jsonevals/scenario-1/

{
  "context": "This criteria evaluates how well the engineer uses the Levenshtein package's Jaro similarity function to solve the name matching problem. The evaluation focuses specifically on correct usage of the jaro() function and appropriate application of its output for comparing and filtering names.",
  "type": "weighted_checklist",
  "checklist": [
    {
      "name": "Uses jaro function",
      "description": "The implementation imports and uses Levenshtein.jaro() function to calculate similarity between strings",
      "max_score": 40
    },
    {
      "name": "Case-insensitive comparison",
      "description": "The implementation correctly handles case-insensitive name comparison by converting strings to lowercase before passing to jaro()",
      "max_score": 15
    },
    {
      "name": "Threshold filtering",
      "description": "The find_matches function correctly filters candidates by comparing jaro() output against the threshold parameter using >= comparison",
      "max_score": 20
    },
    {
      "name": "Maximum similarity selection",
      "description": "The find_best_match function correctly identifies the candidate with the highest jaro() similarity score",
      "max_score": 15
    },
    {
      "name": "Return value correctness",
      "description": "Functions return the correct types and values: calculate_similarity returns float, find_matches returns list in original order, find_best_match returns single string",
      "max_score": 10
    }
  ]
}