Single Agent Pattern - Kore.ai Docs

A streamlined orchestration model where one agent handles all requests.

Overview

The single agent pattern routes all user requests directly to one agent without multi-agent coordination. This agent independently manages:

Intent understanding
Knowledge retrieval
Tool invocation
Response generation

User Request → Agent → Tools/Knowledge → Response

No delegation, no handoffs, no orchestration overhead.

When to Use

Single agent is the right choice when:

Your app has one primary capability or domain.
Tasks are straightforward and don’t require specialists.
Tasks involve closely related actions within one scope.
Low latency is critical.
You want minimal complexity.

Good Fit Examples

Use Case	Why Single Agent Works
Leave management	All requests (check balance, apply, cancel) fall within one domain
FAQ bot	Questions map to a single knowledge base
Order lookup	All actions relate to order data
Appointment scheduling	Booking, rescheduling, cancellation are related tasks

Architecture

Execution Flow

User submits request to the application.
Request routes directly to the single agent (no orchestrator selection).
Agent processes the request:
- Parses user intent
- Determines required actions
- Retrieves relevant knowledge
- Selects and invokes tools
- Generates contextual response
Response returns to user.

Example Conversation

User: "How many vacation days do I have left?"

Agent Processing:
├── Intent: Check leave balance
├── Knowledge: None needed
├── Tool: get_leave_balance(user_id)
└── Response: Generate balance summary

Agent: "You have 12 vacation days remaining this year.
        You've used 8 days so far, and your anniversary
        reset is on March 15th."

Configuration

orchestration:
  pattern: single_agent
  agent: leave_assistant

agents:
  leave_assistant:
    name: Leave Assistant
    description: |
      Handles all employee leave-related requests including
      balance checks, applications, cancellations, and policy questions.

    model: gpt-4o
    context_window: 50

    tools:
      - get_leave_balance
      - apply_for_leave
      - cancel_leave_request
      - get_upcoming_holidays

    knowledge:
      - leave_policies
      - company_calendar

For details, see Orchestration Configuration.

Benefits

Benefit	Description
Simplicity	No orchestration complexity. One agent, direct execution.
Low Latency	No agent selection overhead. Requests process immediately.
Easy Maintenance	Single point of configuration and debugging.
Predictable Behavior	Clear scope boundaries make testing straightforward.

Limitations

Limitation	Mitigation
Single Point of Failure	Add fallback handling or upgrade to a multi-agent pattern
Scope Creep	Define clear boundaries; upgrade pattern when scope expands
No Specialization	Use multi-agent pattern for complex, multi-domain tasks

When to Upgrade

Consider moving to multi-agent patterns when:

Requests frequently fall outside the agent’s scope.
Response quality suffers from broad responsibilities.
You need parallel execution for complex tasks.
Different tasks require different model capabilities.
You want specialized agents for specific domains.

Example: Leave Management Assistant

name: Leave Assistant
description: Complete leave management for employees

scope: |
  ## Responsibilities
  - Check leave balances (vacation, sick, personal)
  - Process leave applications
  - Cancel pending requests
  - Answer policy questions
  - Show team calendar availability

instructions: |
  You help employees manage their leave.

  Guidelines:
  - Always confirm dates before processing requests
  - Check team calendar for conflicts before approving
  - Remind users of blackout dates when relevant
  - Provide remaining balance after any changes

tools:
  - name: get_leave_balance
    description: Get current leave balances for an employee

  - name: apply_for_leave
    description: Submit a new leave request

  - name: cancel_leave
    description: Cancel a pending leave request

  - name: get_team_calendar
    description: Show team availability for date range

knowledge:
  - leave_policies
  - holiday_calendar

​Overview

​When to Use

​Good Fit Examples

​Architecture

​Execution Flow

​Example Conversation

​Configuration

​Benefits

​Limitations

​When to Upgrade

​Example: Leave Management Assistant