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A streamlined orchestration model where one agent handles all requests.

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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.

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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.

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Good Fit Examples

Use CaseWhy Single Agent Works
Leave managementAll requests (check balance, apply, cancel) fall within one domain
FAQ botQuestions map to a single knowledge base
Order lookupAll actions relate to order data
Appointment schedulingBooking, rescheduling, cancellation are related tasks

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Architecture

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Execution Flow

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

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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."

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Configuration

# app-config.yaml
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

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Benefits

BenefitDescription
SimplicityNo orchestration complexity. One agent, direct execution.
Low LatencyNo agent selection overhead. Requests process immediately.
Easy MaintenanceSingle point of configuration and debugging.
Predictable BehaviorClear scope boundaries make testing straightforward.

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Limitations

LimitationMitigation
Single Point of FailureAdd fallback handling or upgrade to a multi-agent pattern
Scope CreepDefine clear boundaries; upgrade pattern when scope expands
No SpecializationUse multi-agent pattern for complex, multi-domain tasks

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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.

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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