[ aws . bedrock-agentcore-control ]
Creates a custom evaluator for agent quality assessment. Custom evaluators use LLM-as-a-Judge configurations with user-defined prompts, rating scales, and model settings to evaluate agent performance at tool call, trace, or session levels.
See also: AWS API Documentation
create-evaluator uses document type values. Document types follow the JSON data model where valid values are: strings, numbers, booleans, null, arrays, and objects. For command input, options and nested parameters that are labeled with the type document must be provided as JSON. Shorthand syntax does not support document types.
create-evaluator
[--client-token <value>]
--evaluator-name <value>
[--description <value>]
--evaluator-config <value>
--level <value>
[--cli-input-json | --cli-input-yaml]
[--generate-cli-skeleton <value>]
[--debug]
[--endpoint-url <value>]
[--no-verify-ssl]
[--no-paginate]
[--output <value>]
[--query <value>]
[--profile <value>]
[--region <value>]
[--version <value>]
[--color <value>]
[--no-sign-request]
[--ca-bundle <value>]
[--cli-read-timeout <value>]
[--cli-connect-timeout <value>]
[--cli-binary-format <value>]
[--no-cli-pager]
[--cli-auto-prompt]
[--no-cli-auto-prompt]
--client-token (string)
A unique, case-sensitive identifier to ensure that the API request completes no more than one time. If you don’t specify this field, a value is randomly generated for you. If this token matches a previous request, the service ignores the request, but doesn’t return an error. For more information, see Ensuring idempotency .
Constraints:
- min:
33- max:
256- pattern:
[a-zA-Z0-9](-*[a-zA-Z0-9]){0,256}
--evaluator-name (string) [required]
The name of the evaluator. Must be unique within your account.
Constraints:
- pattern:
[a-zA-Z][a-zA-Z0-9_]{0,47}
--description (string)
The description of the evaluator that explains its purpose and evaluation criteria.
Constraints:
- min:
1- max:
200
--evaluator-config (tagged union structure) [required]
The configuration for the evaluator, including LLM-as-a-Judge settings with instructions, rating scale, and model configuration.
Note
This is a Tagged Union structure. Only one of the following top level keys can be set:llmAsAJudge.llmAsAJudge -> (structure)
The LLM-as-a-Judge configuration that uses a language model to evaluate agent performance based on custom instructions and rating scales.
instructions -> (string) [required]
The evaluation instructions that guide the language model in assessing agent performance, including criteria and evaluation guidelines.ratingScale -> (tagged union structure) [required]
The rating scale that defines how the evaluator should score agent performance, either numerical or categorical.
Note
This is a Tagged Union structure. Only one of the following top level keys can be set:numerical,categorical.numerical -> (list)
The numerical rating scale with defined score values and descriptions for quantitative evaluation.
(structure)
The definition of a numerical rating scale option that provides a numeric value with its description for evaluation scoring.
definition -> (string) [required]
The description that explains what this numerical rating represents and when it should be used.value -> (double) [required]
The numerical value for this rating scale option.
Constraints:
- min:
0label -> (string) [required]
The label or name that describes this numerical rating option.
Constraints:
- min:
1- max:
100categorical -> (list)
The categorical rating scale with named categories and definitions for qualitative evaluation.
(structure)
The definition of a categorical rating scale option that provides a named category with its description for evaluation scoring.
definition -> (string) [required]
The description that explains what this categorical rating represents and when it should be used.label -> (string) [required]
The label or name of this categorical rating option.
Constraints:
- min:
1- max:
100modelConfig -> (tagged union structure) [required]
The model configuration that specifies which foundation model to use and how to configure it for evaluation.
Note
This is a Tagged Union structure. Only one of the following top level keys can be set:bedrockEvaluatorModelConfig.bedrockEvaluatorModelConfig -> (structure)
The Amazon Bedrock model configuration for evaluation.
modelId -> (string) [required]
The identifier of the Amazon Bedrock model to use for evaluation. Must be a supported foundation model available in your region.inferenceConfig -> (structure)
The inference configuration parameters that control model behavior during evaluation, including temperature, token limits, and sampling settings.
maxTokens -> (integer)
The maximum number of tokens to generate in the model response during evaluation.
Constraints:
- min:
1temperature -> (float)
The temperature value that controls randomness in the model’s responses. Lower values produce more deterministic outputs.
Constraints:
- min:
0- max:
1topP -> (float)
The top-p sampling parameter that controls the diversity of the model’s responses by limiting the cumulative probability of token choices.
Constraints:
- min:
0- max:
1stopSequences -> (list)
The list of sequences that will cause the model to stop generating tokens when encountered.
Constraints:
- min:
0- max:
2500(string)
Constraints:
- min:
1additionalModelRequestFields -> (document)
Additional model-specific request fields to customize model behavior beyond the standard inference configuration.
JSON Syntax:
{
"llmAsAJudge": {
"instructions": "string",
"ratingScale": {
"numerical": [
{
"definition": "string",
"value": double,
"label": "string"
}
...
],
"categorical": [
{
"definition": "string",
"label": "string"
}
...
]
},
"modelConfig": {
"bedrockEvaluatorModelConfig": {
"modelId": "string",
"inferenceConfig": {
"maxTokens": integer,
"temperature": float,
"topP": float,
"stopSequences": ["string", ...]
},
"additionalModelRequestFields": {...}
}
}
}
}
--level (string) [required]
The evaluation level that determines the scope of evaluation. Valid values are
TOOL_CALLfor individual tool invocations,TRACEfor single request-response interactions, orSESSIONfor entire conversation sessions.Possible values:
TOOL_CALLTRACESESSION
--cli-input-json | --cli-input-yaml (string)
Reads arguments from the JSON string provided. The JSON string follows the format provided by --generate-cli-skeleton. If other arguments are provided on the command line, those values will override the JSON-provided values. It is not possible to pass arbitrary binary values using a JSON-provided value as the string will be taken literally. This may not be specified along with --cli-input-yaml.
--generate-cli-skeleton (string)
Prints a JSON skeleton to standard output without sending an API request. If provided with no value or the value input, prints a sample input JSON that can be used as an argument for --cli-input-json. Similarly, if provided yaml-input it will print a sample input YAML that can be used with --cli-input-yaml. If provided with the value output, it validates the command inputs and returns a sample output JSON for that command. The generated JSON skeleton is not stable between versions of the AWS CLI and there are no backwards compatibility guarantees in the JSON skeleton generated.
--debug (boolean)
Turn on debug logging.
--endpoint-url (string)
Override command’s default URL with the given URL.
--no-verify-ssl (boolean)
By default, the AWS CLI uses SSL when communicating with AWS services. For each SSL connection, the AWS CLI will verify SSL certificates. This option overrides the default behavior of verifying SSL certificates.
--no-paginate (boolean)
Disable automatic pagination. If automatic pagination is disabled, the AWS CLI will only make one call, for the first page of results.
--output (string)
The formatting style for command output.
--query (string)
A JMESPath query to use in filtering the response data.
--profile (string)
Use a specific profile from your credential file.
--region (string)
The region to use. Overrides config/env settings.
--version (string)
Display the version of this tool.
--color (string)
Turn on/off color output.
--no-sign-request (boolean)
Do not sign requests. Credentials will not be loaded if this argument is provided.
--ca-bundle (string)
The CA certificate bundle to use when verifying SSL certificates. Overrides config/env settings.
--cli-read-timeout (int)
The maximum socket read time in seconds. If the value is set to 0, the socket read will be blocking and not timeout. The default value is 60 seconds.
--cli-connect-timeout (int)
The maximum socket connect time in seconds. If the value is set to 0, the socket connect will be blocking and not timeout. The default value is 60 seconds.
--cli-binary-format (string)
The formatting style to be used for binary blobs. The default format is base64. The base64 format expects binary blobs to be provided as a base64 encoded string. The raw-in-base64-out format preserves compatibility with AWS CLI V1 behavior and binary values must be passed literally. When providing contents from a file that map to a binary blob fileb:// will always be treated as binary and use the file contents directly regardless of the cli-binary-format setting. When using file:// the file contents will need to properly formatted for the configured cli-binary-format.
--no-cli-pager (boolean)
Disable cli pager for output.
--cli-auto-prompt (boolean)
Automatically prompt for CLI input parameters.
--no-cli-auto-prompt (boolean)
Disable automatically prompt for CLI input parameters.
evaluatorArn -> (string)
The Amazon Resource Name (ARN) of the created evaluator.
Constraints:
- pattern:
arn:aws:bedrock-agentcore:[a-z0-9-]+:[0-9]{12}:evaluator\/[a-zA-Z][a-zA-Z0-9-_]{0,99}-[a-zA-Z0-9]{10}
evaluatorId -> (string)
The unique identifier of the created evaluator.
Constraints:
- pattern:
(Builtin.[a-zA-Z0-9_-]+|[a-zA-Z][a-zA-Z0-9-_]{0,99}-[a-zA-Z0-9]{10})
createdAt -> (timestamp)
The timestamp when the evaluator was created.
status -> (string)
The status of the evaluator creation operation.
Possible values:
ACTIVECREATINGCREATE_FAILEDUPDATINGUPDATE_FAILEDDELETING