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.
Scanned 9/6/2026
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---
name: twilio-taskrouter-routing
description: >
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.
---
## 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.
---
## 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`
---
## Quickstart
**Step 1 — Create a Workspace**
A Workspace is the top-level container for all TaskRouter resources.
**Python**
```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**
```node
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**
```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**
```python
worker = client.taskrouter.v1.workspaces(workspace_sid).workers.create(
friendly_name="Alice",
attributes='{"skills": ["billing", "technical"], "languages": ["en", "es"], "department": "support"}'
)
```
**Node.js**
```node
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**
```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**
```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**
```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)**
```python
@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)**
```node
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:
```python
# 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:
```python
# 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:
```python
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
```python
# 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 |
---
## Gotchas
### 1. Hyphens in Attribute Names Break Silently
```python
# 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
```python
# 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:
```python
@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 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
---
## 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`
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