Update Metric
Partially update a metric. Same field shape as create — see metrics_create for details.
Authorizations
API Key Authentication. It should be included in the header of each request.
Path Parameters
A unique integer value identifying this metric.
Body
URL-friendly unique identifier in snake_case format
255Name 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"
Type 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 Judge
basic, custom_prompt, custom_code, llm_judge binary- Binarycontinuous_qualitative- Continuous Qualitativenumeric- Numericenum- Enum
binary, continuous_qualitative, numeric, enum 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 <= 2147483647Python custom code for the metric. Example:
_resul = True
_explanation = None
if "call_end_reason" in data and data["call_end_reason"] == "customer_satisfaction":
_result = True
_explanation = "Customer expressed satisfaction with service"always- Alwaysautomatic- Automaticcustom- Custom
always, automatic, custom llm_judge- LLM Judgecustom_code- Custom Code
llm_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.
Custom configuration parameters for specific metrics if metric supports it. Example:
- For Infrastructure issues
{
"infra_issues_timeout": 10
}List of knowledge base file IDs for the metric.
Example: [123, 456]
Enable alerts for this metric when it fails (value=false).
Only applicable to binary metrics (eval_type=binary).
For other metric types, use significant_change_alert_status instead.
Example: true or false
disabled- Alerts Disablednormal- Normal Alertssignificant_change- Significant Change Alerts
disabled, normal, significant_change Alert status: enabled or disabled.
enabled- Enableddisabled- Disabled
enabled, disabled Alert direction: increase only, decrease only, or both (empty = both).
Example: "increase", "decrease", or "both"
- `` - Both (Increase and Decrease)
increase- Increase Onlydecrease- Decrease Only
increase, decrease When enabled, this metric is automatically assigned to new agents created in the project.
Filters to apply before computing alerts (CallLogQueryFilter format)
Slack workspace to send alerts to
Override channel ID for this metric's alerts
255For observability_dropoff: when true, copies the dropoff_nodes from configuration to every other agent in the project.
If true, this metric is added to the project's call-success rubric on save (a sensible default rule is chosen by eval_type). If false on an existing rubric metric, it's removed from the rubric.
Response
Name of the metric.
Example: "Customer Satisfaction" or "Appointment Booking"
255binary- Binarycontinuous_qualitative- Continuous Qualitativenumeric- Numericenum- Enum
binary, continuous_qualitative, numeric, enum URL-friendly unique identifier in snake_case format. Example: "customer_satisfaction_1562"
255Description of what the metric measures.
Example: "Measures how satisfied customers are with the service provided"
Type 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 Judge
basic, custom_prompt, custom_code, llm_judge List of possible enum values for enum type metrics.
Example: ["satisfied", "unsatisfied"]
Whether this metric requires audio analysis.
Example: true or false
Evaluation prompt for the metric.
Example: "Evaluate customer satisfaction based on conversation"
always- Alwaysautomatic- Automaticcustom- Custom
always, automatic, custom Type of trigger evaluation: LLM judge or custom code.
Only used when evaluation_trigger is CUSTOM.
Example: "llm_judge" or "custom_code"
llm_judge- LLM Judgecustom_code- Custom Code
llm_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.
Custom configuration parameters for specific metrics if metric supports it. Example:
- For Infrastructure issues
{
"infra_issues_timeout": 10
}The overall score for this metric across all test sets
The total score for this metric
Knowledge base files associated with this metric
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
Enable alerts for this metric when it fails (value=false).
Only applicable to binary metrics (eval_type=binary).
For other metric types, use significant_change_alert_status instead.
Example: true or false
disabled- Alerts Disablednormal- Normal Alertssignificant_change- Significant Change Alerts
disabled, normal, significant_change Filters to apply before computing alerts (CallLogQueryFilter format)
Slack workspace to send alerts to
Override channel ID for this metric's alerts
255Alert status: enabled or disabled.
enabled- Enableddisabled- Disabled
enabled, disabled Alert direction: increase only, decrease only, or both (empty = both).
Example: "increase", "decrease", or "both"
- `` - Both (Increase and Decrease)
increase- Increase Onlydecrease- Decrease Only
increase, decrease Predefined function name
Example: "get_latency" or "check_critical_deviations"
255Python custom code for the metric. Example:
_resul = True
_explanation = None
if "call_end_reason" in data and data["call_end_reason"] == "customer_satisfaction":
_result = True
_explanation = "Customer expressed satisfaction with service"Vocera defined metric code for the metric.
Example: "7fd534f5"
255Reviews associated with the metric
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.
Unsaved proposal from a metric-optimiser cron run. Shape: {description, evaluation_trigger, type, custom_code, score, baseline_score, cron_job_id, cron_job_name, proposed_at}.