Customer Query Routing and Handoff

# Agent Handoff Chain
# Classify customer queries and route to the right specialist agent.
osop_version: "2.0"
id: agent-handoff-chain
name: Customer Query Routing and Handoff

nodes:
  - id: customer_query
    type: system
    purpose: Receive and normalize incoming customer query
    runtime:
      tool: message-queue
    outputs:
      - query_text
      - customer_id

  - id: classifier
    type: agent
    purpose: Classify query intent into support, sales, or technical category
    runtime:
      provider: anthropic
      model: claude-haiku-4-20250414
    inputs:
      - query_text
    outputs:
      - category
      - confidence
    timeout_sec: 10
    explain: "Fast, cheap model for classification. Falls back to human if confidence < 0.7."

  - id: router
    type: system
    subtype: router
    purpose: Route query to the appropriate specialist based on classification
    runtime:
      tool: workflow-router
    inputs:
      - category
      - confidence

  - id: support_agent
    type: agent
    purpose: Handle billing, account, and general support queries
    runtime:
      provider: anthropic
      model: claude-sonnet-4-20250514
    inputs:
      - query_text
      - customer_id
    outputs:
      - response_draft
    handoff:
      from: classifier
      context_keys: [query_text, category, customer_id]

  - id: sales_agent
    type: agent
    purpose: Handle pricing, upgrade, and purchase queries
    runtime:
      provider: openai
      model: gpt-4o
    inputs:
      - query_text
      - customer_id
    outputs:
      - response_draft
    handoff:
      from: classifier
      context_keys: [query_text, category, customer_id]

  - id: technical_agent
    type: agent
    purpose: Handle API issues, debugging, and technical integration queries
    runtime:
      provider: anthropic
      model: claude-sonnet-4-20250514
    inputs:
      - query_text
      - customer_id
    outputs:
      - response_draft
    handoff:
      from: classifier
      context_keys: [query_text, category, customer_id]

  - id: quality_check
    type: agent
    purpose: Review specialist response for tone, accuracy, and completeness
    runtime:
      provider: anthropic
      model: claude-haiku-4-20250414
    inputs:
      - response_draft
      - query_text
    outputs:
      - quality_score
      - final_response

  - id: human_escalation
    type: human
    purpose: Handle low-confidence classifications or failed quality checks
    role: senior_agent
    inputs:
      - query_text
      - customer_id
    outputs:
      - final_response
    explain: "Escalation path when automation confidence is too low."

edges:
  - from: customer_query
    to: classifier
    mode: sequential

  - from: classifier
    to: router
    mode: sequential

  - from: router
    to: support_agent
    mode: conditional
    condition: "category == 'support'"

  - from: router
    to: sales_agent
    mode: conditional
    condition: "category == 'sales'"

  - from: router
    to: technical_agent
    mode: conditional
    condition: "category == 'technical'"

  - from: router
    to: human_escalation
    mode: conditional
    condition: "confidence < 0.7"
    explain: "Low-confidence queries go to a human agent."

  - from: support_agent
    to: quality_check
    mode: sequential

  - from: sales_agent
    to: quality_check
    mode: sequential

  - from: technical_agent
    to: quality_check
    mode: sequential

  - from: quality_check
    to: human_escalation
    mode: fallback
    condition: "quality_score < 0.8"