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Documentation Index

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​
Endpoint

​
method
string
default:"GET"
GET
​
endpoint
string
/v1/evaluator/{evaluatorId}/stats

​
Authentication

This endpoint requires API key authentication. Include your API key in the request headers: 
Authorization: Bearer YOUR_API_KEY

​
Path Parameters

​
evaluatorId
string
required
The unique identifier of the evaluator

​
Response

​
data
object
Evaluator statistics
​
averageScore
number
Average score across all evaluations
​
totalUses
number
Total number of times this evaluator has been used
​
recentTrend
string
Recent trend direction: “up”, “down”, or “stable”
​
scoreDistribution
array
Distribution of scores across ranges
​
range
string
Score range (e.g., “0-20”, “20-40”)
​
count
number
Number of evaluations in this range
​
timeSeriesData
array
Historical data over time
​
date
string
Date in ISO format
​
value
number
Average score for that date
​
error
string | null
Error message if the request failed, null otherwise

​
Example Request

curl -X GET https://api.helicone.ai/v1/evaluator/eval_abc123/stats \
  -H "Authorization: Bearer YOUR_API_KEY"

​
Example Response

{
  "data": {
    "averageScore": 7.5,
    "totalUses": 1250,
    "recentTrend": "up",
    "scoreDistribution": [
      {
        "range": "0-2",
        "count": 50
      },
      {
        "range": "2-4",
        "count": 100
      },
      {
        "range": "4-6",
        "count": 200
      },
      {
        "range": "6-8",
        "count": 450
      },
      {
        "range": "8-10",
        "count": 450
      }
    ],
    "timeSeriesData": [
      {
        "date": "2024-01-01",
        "value": 7.2
      },
      {
        "date": "2024-01-02",
        "value": 7.3
      },
      {
        "date": "2024-01-03",
        "value": 7.4
      },
      {
        "date": "2024-01-04",
        "value": 7.6
      },
      {
        "date": "2024-01-05",
        "value": 7.5
      }
    ]
  },
  "error": null
}

​
Use Cases

  • Monitor evaluator performance over time
  • Identify trends in evaluation scores
  • Understand score distribution patterns
  • Track usage frequency of different evaluators
  • Optimize evaluation criteria based on historical data

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