This API is used to list all the metrics associated with an agent or a project or both.
Filtering behavior:
API Key Authentication. It should be included in the header of each request.
Filter by agent ID
Example: 123
Filter by project ID
Example: 456
Filter by assistant ID
Example: asst_1234567890
Filter metrics by agent IDs. Supports comma-separated list.
Example: 1,2,3 to filter metrics associated with any of these agents
JSON filter parameter for advanced filtering.
Example:
{"operator":"and","conditions":[{"field":"agents__id","op":"in","value":[1,2,3]}]}Supported fields: agents__id, eval_type, type, name Supported operators: in, eq, contains
Include Overall and Total scores in Metric List
Example: true or false
Name of the AI agent that was tested
Example: "Test Agent 1"
Name of the metric.
Example: "Customer Satisfaction" or "Appointment Booking"
255Description of what the metric measures.
Example: "Measures how satisfied customers are with the service provided"
Predefined function name
Example: "get_latency" or "check_critical_deviations"
255Type of metric
basic - Basic (Deprecated in favor of LLM Judge)custom_prompt - Custom Prompt ( Deprecated in favor of LLM Judge)custom_code - Custom Codellm_judge - LLM Judgebasic, custom_prompt, custom_code, llm_judge Type of evaluation
binary_workflow_adherence - Binary Workflow Adherencebinary_qualitative - Binary Qualitativecontinuous_qualitative - Continuous Qualitativenumeric - Numericenum - Enumbinary_workflow_adherence, binary_qualitative, continuous_qualitative, numeric, enum List of possible enum values for enum type metrics.
Example: ["satisfied", "unsatisfied"]
Whether this metric requires audio analysis.
Example: true or false
Enable this metric for observability.
Example: true or false
Enable this metric for simulations.
Example: true or false
Enable sampling for this metric using project-level sample rate
Evaluation prompt for the metric.
Example: "Evaluate customer satisfaction based on conversation"
Display order for the metric.
Example: 1
-2147483648 <= x <= 2147483647always - Alwaysautomatic - Automaticcustom - Customalways, automatic, custom llm_judge - LLM Judgecustom_code - Custom Codellm_judge, custom_code Evaluation trigger prompt for the metric.
Example: "Evaluate metric only if call ended reason is main-agent-ended-call"
Python custom code to determine metric relevance. Code should set _result (bool) and _explanation (str). Example:
_result = True
_explanation = "Metric is relevant"
if "call_end_reason" in data and data["call_end_reason"] == "customer-hung-up":
_result = False
_explanation = "Customer hung up, metric not applicable"Priority assignment prompt for the metric.
Vocera defined metric code for the metric.
Example: "7fd534f5"
255Custom configuration parameters for specific metrics if metric supports it. Example:
{
"infra_issues_timeout": 10
}List of knowledge base file IDs for the metric.
Example: [123, 456]
Metric Cost
Example: 0.10
disabled - Alerts Disablednormal - Normal Alertssignificant_change - Significant Change Alertsdisabled, normal, significant_change Alert status: enabled or disabled.
enabled - Enableddisabled - Disabledenabled, disabled Alert direction: increase only, decrease only, or both (empty = both).
Example: "increase", "decrease", or "both"
increase - Increase Onlydecrease - Decrease Only, increase, decrease Window size for rolling statistics calculation.
Example: 50
Standard deviation multiplier for threshold calculation.
Example: 2.0
Alpha value for exponentially weighted moving average (EWMA) calculation.
Example: 0.1
When enabled, this metric is automatically assigned to new agents created in the project.