bedrockagentcore_start_recommendation: Starts a recommendation job that analyzes agent traces and...

In paws.machine.learning: 'Amazon Web Services' Machine Learning Services

Starts a recommendation job that analyzes agent traces and generates optimization suggestions for system prompts or tool descriptions to improve agent performance

Description

Starts a recommendation job that analyzes agent traces and generates optimization suggestions for system prompts or tool descriptions to improve agent performance.

See https://www.paws-r-sdk.com/docs/bedrockagentcore_start_recommendation/ for full documentation.

Usage

bedrockagentcore_start_recommendation(
  name,
  description = NULL,
  type,
  recommendationConfig,
  kmsKeyArn = NULL,
  clientToken = NULL,
  tags = NULL
)

Arguments

name	[required] The name of the recommendation. Must be unique within your account.
description	The description of the recommendation.
type	[required] The type of recommendation to generate. Valid values are SYSTEM_PROMPT_RECOMMENDATION for system prompt optimization or TOOL_DESCRIPTION_RECOMMENDATION for tool description optimization.
recommendationConfig	[required] The configuration for the recommendation, including the input to optimize, agent traces to analyze, and evaluation settings.
kmsKeyArn	The ARN of the KMS key used to encrypt recommendation data. If provided, customer data is encrypted at rest with the specified key.
clientToken	A unique, case-sensitive identifier to ensure that the API request completes no more than one time. If this token matches a previous request, the service ignores the request, but does not return an error.
tags	A map of tag keys and values to associate with the recommendation.

paws.machine.learning documentation built on Oct. 8, 2026, 9:06 a.m.