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twilio-taskrouter-routing

✓ Official4,081

by openai · part of openai/plugins

Route tasks to agents using Twilio TaskRouter. Covers Workers, Task Queues, Workflows, Reservations, skills-based routing, and common gotchas (hyphen attributes, HAS operator, reservation cascade). Use this skill for any multi-agent contact center, support queue, or AI agent escalation routing.

🧩 One of 7 skills in the openai/plugins package — works on its own, and pairs well with its siblings.

This is the playbook your agent receives when the skill activates — you don't need to read it to use the skill, but it's here to audit before installing.

Overview

TaskRouter is Twilio's skills-based routing engine. Instead of building custom queuing logic, you define Workers (agents), Task Queues (groups), and Workflows (routing rules). TaskRouter matches incoming tasks to the best available worker.

Incoming Task → Workflow (routing rules) → Task Queue (skill match) → Worker (agent)
                                                                        ↓
                                                                   Reservation
                                                                   (accept/reject)

Common mistake: Developers reinvent TaskRouter in custom Node.js — don't. If you're building skills-based routing, queue management, or agent assignment, use TaskRouter.


Key Patterns

Skills-Based Routing

Match tasks to workers based on attributes:

Worker expressionMatches
skills HAS "billing"Workers whose skills array contains "billing"
languages HAS "es"Spanish-speaking workers
department == "support"Workers in support department
experience > 5Workers with 5+ years experience
skills HAS "billing" AND languages HAS "es"Spanish-speaking billing agents

Priority Routing

Tasks with higher priority are assigned first:

# VIP customer — priority 10 (higher = first)
task = client.taskrouter.v1.workspaces(workspace_sid).tasks.create(
    attributes='{"department": "billing", "priority": 10, "vip": true}',
    workflow_sid=workflow.sid,
    priority=10
)

AI Agent Escalation

When an AI agent (via TAC) escalates to a human, create a TaskRouter task with the AI's context:

# From your escalation webhook handler
def handle_escalation(escalation_data):
    task = client.taskrouter.v1.workspaces(workspace_sid).tasks.create(
        attributes=json.dumps({
            "department": escalation_data["reason_code"],
            "conversation_id": escalation_data["conversation_id"],
            "profile_id": escalation_data["profile_id"],
            "ai_summary": escalation_data["summary"],
            "priority": 5
        }),
        workflow_sid=workflow.sid
    )

The human agent receives the AI's conversation summary and customer profile.

Workflow with Timeout Escalation

Route to specialized queue first, then overflow to general:

workflow_config = {
    "task_routing": {
        "filters": [
            {
                "filter_friendly_name": "Billing Specialist First",
                "expression": "department == 'billing'",
                "targets": [
                    {"queue": billing_queue.sid, "timeout": 60},      # Try billing queue for 60s
                    {"queue": default_queue.sid, "timeout": 120}      # Overflow to general
                ]
            }
        ],
        "default_filter": {
            "queue": default_queue.sid
        }
    }
}

Worker Activity Management

# Set worker to available
client.taskrouter.v1.workspaces(workspace_sid) \
    .workers(worker_sid) \
    .update(activity_sid=available_activity_sid)

# Get real-time worker statistics
stats = client.taskrouter.v1.workspaces(workspace_sid) \
    .workers \
    .statistics() \
    .fetch()

print(f"Available: {stats.realtime['total_available_workers']}")

Scale Guidance

AgentsArchitectureNotes
< 10Single workflow, one queue per skillNo Flex needed — agents use phone
10-50Multi-queue workflows, skills-based routingFlex recommended for desktop
50+Multi-tier workflows, priority routing, real-time monitoringFull Flex + supervisor tools

Gotchas

1. Hyphens in Attribute Names Break Silently

# WRONG — hyphens in attribute keys break workflow expressions
worker = client.taskrouter.v1.workspaces(workspace_sid).workers.create(
    friendly_name="Alice",
    attributes='{"skill-level": 5}'  # hyphen breaks expression evaluation
)

# RIGHT — use underscores or camelCase
worker = client.taskrouter.v1.workspaces(workspace_sid).workers.create(
    friendly_name="Alice",
    attributes='{"skill_level": 5}'
)

No error — the expression silently fails to match.

2. HAS Operator on Non-Array Attributes

# WRONG — "billing" is a string, not an array. HAS silently matches nothing.
target_workers = 'department HAS "billing"'

# RIGHT — use == for string attributes
target_workers = 'department == "billing"'

# RIGHT — use HAS only for arrays
target_workers = 'skills HAS "billing"'  # skills: ["billing", "technical"]

Tasks sit in queue forever with no error.

3. Reservation Timeout Cascade

When a reservation times out:

  1. Worker moves to the timeout Activity (often "Offline")
  2. Fewer workers available → other reservations also time out
  3. Positive feedback loop → entire queue backs up

Fix: Set the timeout Activity to a short-duration state, not "Offline". Or implement a reservation timeout handler that keeps the worker available:

@app.route("/taskrouter-events", methods=["POST"])
def taskrouter_event():
    event_type = request.form["EventType"]
    if event_type == "reservation.timeout":
        worker_sid = request.form["WorkerSid"]
        # Keep worker available instead of moving to offline
        client.taskrouter.v1.workspaces(workspace_sid) \
            .workers(worker_sid) \
            .update(activity_sid=available_activity_sid)
    return "", 200

4. Activity Available Flag

Updating an Activity's available flag returns 200 OK but may not change the value if workers are currently in that activity. Create new activities instead of modifying existing ones.


CANNOT

  • Hyphens in attribute names break expressionsskill-level is treated as subtraction (skill minus level). Error 20001. Always use underscores: skill_level.
  • HAS on non-array silently matches nothingdepartment HAS "billing" on a string attribute is accepted at creation but never matches. Tasks sit in queue forever with no error.
  • Expression validation is syntactic only — Queue creation validates parse but NOT worker matching. Semantically wrong expressions create successfully with zero matching workers.
  • Activity available flag is silently immutable — Updating returns 200 OK but does not change the value. Must delete and recreate the Activity.
  • multiTaskEnabled cannot be reverted to false — Once enabled on a Workspace, cannot be disabled. One-way door.
  • Reservation timeout moves worker to timeout Activity — Worker automatically moved to Offline. Must manually set back. This cascades: fewer available workers → more timeouts → queue collapse. See Gotcha #3.
  • Workflow target timeout auto-cancels tasks — When all targets exhaust timeouts, task is canceled. Always include a default_filter as catch-all.
  • Worker friendlyName is case-insensitive unique — "alice" collides with "Alice".
  • workflowSid is required for task creation — API does not auto-select a default Workflow.
  • Cannot update task status and attributes in same request — Must be two separate API calls.
  • Assignment callback must respond in 5 seconds — If both primary and fallback URLs fail, reservation is canceled.
  • Tasks auto-cancel after 1,000 rejections — If a task cycles through 1,000 reservation rejections, it is automatically canceled.
  • page query param not supported — Use PageToken for pagination. page returns error 40153.
  • Cannot use malformed JSON in worker attributes — Silently breaks matching with no error
  • Cannot use regex in workflow expressions — Only supports ==, !=, <, >, HAS, IN, CONTAINS, AND, OR, NOT
  • Cannot exceed 50,000 Workers per Workspace — Hard limit
  • Cannot exceed 250 Task Queues per Workspace — Hard limit
  • Cannot delay reservation callback response beyond 15 seconds — Timeout results in reservation failure

Next Steps

  • Conference for transfers: twilio-conference-calls
  • Call recording: twilio-call-recordings
  • AI agent voice integration: twilio-voice-conversation-relay
  • Voice IVR before routing: twilio-voice-twiml