Agent

apiVersion: ark.mckinsey.com/v1alpha1
kind: Agent
metadata:
  name: example-agent
spec:
  # Agent's system prompt that defines its behavior
  prompt: |
    You are a helpful assistant.
    
  # Human-readable description
  description: General-purpose assistant agent
  
  # Model reference (optional - defaults to 'default' if not specified)
  modelRef:
    name: gpt-4-model
    namespace: default
    
  # Execution engine (optional - uses built-in OpenAI-compatible engine if not specified)
  executionEngine:
    name: langchain-engine
    namespace: default
    
  # Tools the agent can use
  tools:
    - type: built-in  # System-provided tools (web-search, calculations)
      name: web-search
    - type: custom   # References to Tool or MCPServer resources
      name: my-custom-tool
      
  # Parameters for template processing in prompts
  parameters:
    - name: api_endpoint
      valueFrom:
        configMapKeyRef:
          name: config
          key: endpoint
    - name: agent_name
      valueFrom:
        queryParameterRef:
          name: agent_name
          
  # JSON schema for structured output (optional)
  outputSchema:
    type: object
    properties:
      summary:
        type: string
      confidence:
        type: number
        
status:
  # Status conditions indicate agent health and availability
  conditions:
  - type: Available
    status: "True"
    reason: AllDependenciesReady
    message: Agent is ready for execution

status:
  conditions:
  - type: Available
    status: "True"
    reason: AllDependenciesReady
    message: Agent is ready for execution

apiVersion: ark.mckinsey.com/v1alpha1
kind: Agent
metadata:
  name: simple-agent
spec:
  prompt: You are a helpful assistant.

apiVersion: ark.mckinsey.com/v1alpha1
kind: Agent
metadata:
  name: weather-agent
spec:
  prompt: |
    You are a weather forecasting assistant.
    Use the available tools to get weather information.
  tools:
    - type: custom
      name: get-coordinates
    - type: custom
      name: get-forecast

apiVersion: ark.mckinsey.com/v1alpha1
kind: Agent
metadata:
  name: analyzer
spec:
  prompt: Analyze the input and provide structured feedback.
  outputSchema:
    type: object
    required: [sentiment, confidence]
    properties:
      sentiment:
        type: string
        enum: [positive, negative, neutral]
      confidence:
        type: number
        minimum: 0
        maximum: 1

apiVersion: ark.mckinsey.com/v1alpha1
kind: Agent
metadata:
  name: policy-reviewer
spec:
  prompt: |
    You are a policy review assistant. Review documents according to these guidelines:
    
    Policy documents are located at: {{.policyDocumentsPath}}
    
    Use the following criteria for review:
    {{.reviewCriteria}}
  parameters:
    - name: policyDocumentsPath
      valueFrom:
        configMapKeyRef:
          name: policy-config
          key: documents-path
    - name: reviewCriteria
      valueFrom:
        configMapKeyRef:
          name: policy-config
          key: review-criteria

apiVersion: ark.mckinsey.com/v1alpha1
kind: Agent
metadata:
  name: dynamic-agent
spec:
  prompt: |
    Your name is {{.agent_name}}.
    You operate in {{.mode}} mode.
    Your expertise level is {{.expertise_level}}.
  parameters:
    - name: agent_name
      valueFrom:
        queryParameterRef:  # Resolved from Query's parameters at runtime
          name: agent_name
    - name: mode
      valueFrom:
        queryParameterRef:
          name: operation_mode
    - name: expertise_level
      value: "expert"  # Static value

apiVersion: ark.mckinsey.com/v1alpha1
kind: Agent
metadata:
  name: aws-operator-agent
  annotations:
    # A2A server that created this agent
    ark.mckinsey.com/a2a-server-name: aws-operator-agent
    # Resolved address of the A2A server
    ark.mckinsey.com/a2a-server-address: http://ark-agentcore-bridge.default.svc.cluster.local:80/a2a/agent/aws_operator_agent-jg0yD9Hv2n
    # Skills discovered from the A2A server
    ark.mckinsey.com/a2a-server-skills: '[{"name":"describe_ec2_instances","description":"List and describe EC2 instances"}]'
spec:
  description: AWS operations agent with read-only access to AWS services
  prompt: You are aws_operator_agent. AWS operations agent with read-only access to AWS services
  executionEngine:
    name: a2a
  # modelRef omitted - A2A agents don't require models by default
  # If the underlying A2A server uses an ARK model, the agent can optionally link to it via modelRef.
  # When modelRef is set, the agent will only show as Available if both the model and A2A server are available.
  # Otherwise, only the A2A server availability is checked.