{
  "context": "Evaluates whether the solution leverages github.com/prometheus/client_model histogram messages to expose fractional overrides for totals and buckets. It checks that float fields take precedence over integer counters while still producing a valid serialized metric payload.",
  "type": "weighted_checklist",
  "checklist": [
    {
      "name": "Float total override",
      "description": "Sets Histogram.SampleCountFloat to the provided fractional total and ensures SampleCount is only used as a fallback when no override is present.",
      "max_score": 25
    },
    {
      "name": "Bucket float override",
      "description": "Populates Bucket.CumulativeCountFloat for buckets with fractional counts while keeping CumulativeCount as the fallback for buckets without overrides.",
      "max_score": 25
    },
    {
      "name": "Monotonic buckets",
      "description": "Ensures Bucket entries remain non-decreasing (using CumulativeCountFloat when present) and that the final bucket aligns with Histogram.SampleCountFloat or SampleCount.",
      "max_score": 15
    },
    {
      "name": "Integer fallback",
      "description": "Leaves SampleCountFloat and CumulativeCountFloat unset when no overrides are provided and relies on SampleCount and CumulativeCount values without recalculation.",
      "max_score": 15
    },
    {
      "name": "Histogram encoding",
      "description": "Wraps the histogram in a Metric with MetricFamily.Type set to MetricType_HISTOGRAM and serializes via client_model types without custom structs replacing the proto messages.",
      "max_score": 20
    }
  ]
}