twilio-taskrouter-routing — Codex skill: what it does, how to install
Configures task routing for Twilio TaskRouter. Helps set up workspaces, worker skill queues, and workflow rules for contact centers or AI escalations.
npx skills add openai/plugins --skill twilio-taskrouter-routing -a codexWhat twilio-taskrouter-routing does
This skill writes Python and Node.js setup scripts for Twilio TaskRouter. It guides the creation of top-level Workspaces, agent activity states, and Task Queues with attribute expressions.
Tasks route through Workflows using filter rules, priority timeouts, and fallback queues. Once TaskRouter reserves a worker, it triggers your assignment_callback_url. The handler answers with either a direct dequeue or a conference instruction.
Payload generation strictly requires json.dumps() or JSON.stringify(). Raw string formatting introduces JSON injection risks in worker attributes. Running the generated code requires TWILIO_ACCOUNT_SID, TWILIO_AUTH_TOKEN, and the official twilio SDK package.
What it helps with
- route inbound tasks to agents based on worker skills and languages
- set up TaskRouter Workspaces with activities and custom queues
- write Workflow JSON configurations with fallback targets and timeouts
- handle assignment callback webhooks using dequeue or conference responses
Example prompts for the agent
- Create a TaskRouter Workspace in Python with Available, Offline, and On Task activities.
- Define a TaskQueue that matches agents with technical skills using the HAS operator.
- Write an Express route for the assignment callback returning a dequeue instruction.
How to install twilio-taskrouter-routing
1Skills CLI (Vercel)
npx skills add openai/plugins --skill twilio-taskrouter-routing -a codex2Manually: put the files in place
.agents/skills/twilio-taskrouter-routing/SKILL.mdFor all projects use ~/.agents/skills/
1Skills CLI (Vercel)
npx skills add openai/plugins --skill twilio-taskrouter-routing -a claude-code2Manually: put the files in place
~/.claude/skills/twilio-taskrouter-routing/SKILL.mdCopy the whole skill folder; for one project use .claude/skills/twilio-taskrouter-routing/
Manually: put the files in place
.cursor/skills/twilio-taskrouter-routing/SKILL.mdCursor also reads .agents/skills/ and .claude/skills/
1GitHub CLI
gh skill install openai/plugins twilio-taskrouter-routing2Manually: put the files in place
.github/skills/twilio-taskrouter-routing/SKILL.mdPlatform CLI
gemini skills install https://github.com/openai/plugins --path plugins/twilio-developer-kit/skills/twilio-taskrouter-routingManually: put the files in place
.devin/skills/twilio-taskrouter-routing/SKILL.mdThe legacy .windsurf/skills/ path still works
Claude.ai
Zip the folder and upload it in Settings → Capabilities → Skills
Step by step, with commands for each platform: Codex skills: how to install, where they live, how to call them
Questions about twilio-taskrouter-routing
How to install twilio-taskrouter-routing in Codex?
Run npx skills add openai/plugins --skill twilio-taskrouter-routing -a codex in your terminal.
What does twilio-taskrouter-routing do?
It assists in building routing logic with Twilio TaskRouter, matching tasks to agents by skills and handling reservation callbacks.
What dependencies are required for TaskRouter scripts?
You need TWILIO_ACCOUNT_SID and TWILIO_AUTH_TOKEN set in your environment, plus the official twilio library installed via pip or npm.
Source text
SKILL.md · MIT
---
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`
© Twilio · MIT · openai/plugins