openai/twilio-taskrouter-routing

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.

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Prerequisites

• Twilio account — see twilio-account-setup
• TWILIO_ACCOUNT_SID and TWILIO_AUTH_TOKEN — see twilio-iam-auth-setup
• SDK: pip install twilio / npm install twilio
• For voice routing: a Twilio phone number with webhook configured — see twilio-voice-twiml
• For AI escalation: ConversationRelay with escalation tools — see twilio-voice-conversation-relay

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Quickstart

Step 1 — Create a Workspace

A Workspace is the top-level container for all TaskRouter resources.

Python

import os
from twilio.rest import Client

client = Client(os.environ["TWILIO_ACCOUNT_SID"], os.environ["TWILIO_AUTH_TOKEN"])

workspace = client.taskrouter.v1.workspaces.create(
    friendly_name="Support Center",
    event_callback_url="https://yourapp.com/taskrouter-events"
)

workspace_sid = workspace.sid  # WSxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
print(workspace_sid)

Node.js

const twilio = require("twilio");
const client = twilio(process.env.TWILIO_ACCOUNT_SID, process.env.TWILIO_AUTH_TOKEN);

const workspace = await client.taskrouter.v1.workspaces.create({
    friendlyName: "Support Center",
    eventCallbackUrl: "https://yourapp.com/taskrouter-events",
});

const workspaceSid = workspace.sid;

Step 2 — Create Activities (agent states)

Python

# Available — worker can receive tasks
available = client.taskrouter.v1.workspaces(workspace_sid).activities.create(
    friendly_name="Available", available=True
)

# Offline — worker cannot receive tasks
offline = client.taskrouter.v1.workspaces(workspace_sid).activities.create(
    friendly_name="Offline", available=False
)

# On a task — worker is busy
on_task = client.taskrouter.v1.workspaces(workspace_sid).activities.create(
    friendly_name="On Task", available=False
)

Step 3 — Create Workers (agents)

Security: Always use json.dumps() (Python) or JSON.stringify() (Node.js) to construct attribute payloads. String interpolation is vulnerable to JSON injection.

Python

worker = client.taskrouter.v1.workspaces(workspace_sid).workers.create(
    friendly_name="Alice",
    attributes='{"skills": ["billing", "technical"], "languages": ["en", "es"], "department": "support"}'
)

Node.js

const worker = await client.taskrouter.v1.workspaces(workspaceSid).workers.create({
    friendlyName: "Alice",
    attributes: JSON.stringify({
        skills: ["billing", "technical"],
        languages: ["en", "es"],
        department: "support",
    }),
});

Step 4 — Create Task Queues

Python

# Billing queue — matches workers with "billing" skill
billing_queue = client.taskrouter.v1.workspaces(workspace_sid).task_queues.create(
    friendly_name="Billing",
    target_workers='skills HAS "billing"'
)

# Technical queue
tech_queue = client.taskrouter.v1.workspaces(workspace_sid).task_queues.create(
    friendly_name="Technical",
    target_workers='skills HAS "technical"'
)

# Catch-all queue
default_queue = client.taskrouter.v1.workspaces(workspace_sid).task_queues.create(
    friendly_name="Default",
    target_workers='1==1'  # matches all workers
)

Step 5 — Create a Workflow (routing rules)

Python

import json

workflow_config = {
    "task_routing": {
        "filters": [
            {
                "filter_friendly_name": "Billing",
                "expression": "department == 'billing'",
                "targets": [
                    {"queue": billing_queue.sid, "timeout": 120}
                ]
            },
            {
                "filter_friendly_name": "Technical",
                "expression": "department == 'technical'",
                "targets": [
                    {"queue": tech_queue.sid, "timeout": 120}
                ]
            }
        ],
        "default_filter": {
            "queue": default_queue.sid
        }
    }
}

workflow = client.taskrouter.v1.workspaces(workspace_sid).workflows.create(
    friendly_name="Support Routing",
    configuration=json.dumps(workflow_config),
    assignment_callback_url="https://yourapp.com/assignment"
)

Step 6 — Create a Task (from an incoming call)

Python

task = client.taskrouter.v1.workspaces(workspace_sid).tasks.create(
    attributes='{"department": "billing", "caller": "+15558675310", "priority": 1}',
    workflow_sid=workflow.sid
)

Step 7 — Handle the Assignment Callback

When TaskRouter finds a matching worker, it POSTs to your assignment_callback_url:

Python (Flask)

@app.route("/assignment", methods=["POST"])
def assignment():
    task_sid = request.form["TaskSid"]
    worker_sid = request.form["WorkerSid"]
    reservation_sid = request.form["ReservationSid"]

    # Option A: Dequeue to the worker's phone
    return jsonify({
        "instruction": "dequeue",
        "from": "+15551234567",  # your Twilio number
        "post_work_activity_sid": available_activity_sid
    })

    # Option B: Conference the caller and agent
    # return jsonify({
    #     "instruction": "conference",
    #     "from": "+15551234567",
    #     "post_work_activity_sid": available_activity_sid
    # })

Node.js (Express)

app.post("/assignment", (req, res) => {
    res.json({
        instruction: "dequeue",
        from: "+15551234567",
        post_work_activity_sid: availableActivitySid,
    });
});

---

Key Patterns

Skills-Based Routing

Match tasks to workers based on attributes:

| Worker expression | Matches | |-------------------|---------| | skills HAS "billing" | Workers whose skills array contains "billing" | | languages HAS "es" | Spanish-speaking workers | | department == "support" | Workers in support department | | experience > 5 | Workers 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

| Agents | Architecture | Notes | |--------|-------------|-------| | < 10 | Single workflow, one queue per skill | No Flex needed — agents use phone | | 10-50 | Multi-queue workflows, skills-based routing | Flex recommended for desktop | | 50+ | Multi-tier workflows, priority routing, real-time monitoring | Full Flex + supervisor tools |

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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.

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CANNOT

• Hyphens in attribute names break expressions — skill-level is treated as subtraction (skill minus level). Error 20001. Always use underscores: skill_level.
• HAS on non-array silently matches nothing — department 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

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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