Twilio for AI provides coding agents with skills and an MCP server for using Twilio services and documentation. The MCP server searches Twilio documentation and API specifications and retrieves full schemas for selected operations, while the skills supply procedural guidance to agents. Its catalogue add-ons are intended for Claude Code, Cursor, Codex, and other tools that support the Agent Skills standard.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add twilio/ai --skill twilio-studio-flowsgit clone --depth 1 https://github.com/twilio/aiWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/twilio/ai/twilio-studio-flows)<a href="https://agentmods.dev/skills/twilio/ai/twilio-studio-flows"><img src="https://agentmods.dev/badge/skills/twilio/ai/twilio-studio-flows.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Memory Poisoning · line 276 Skill manipulates agent memory, state, or stored context. Memory corruption can alter personality, override safety rules, or cause unpredictable behavior.Fix: Protect agent memory and state from modification by untrusted content. Use read-only memory for critical instructions and validate all state changes.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00094 | $0.04388 |
| Opus 5 | $0.00047 | $0.02194 |
| Sonnet 5 | $0.00019 | $0.00878 |
| Haiku 4.5 | $0.00009 | $0.00439 |
Grade A, and why
twilio-studio-flows scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 419 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Overview
A Studio flow is a state machine Twilio executes in response to an inbound call,
message, conversation, or REST API request. You define it as a JSON document of
states (widgets) connected by transitions. Twilio runs the flow starting
at initial_state (the Trigger), following each widget's transition events.
Inbound call / message / API request
│
▼
Trigger ──incomingCall──▶ Gather ──keypress──▶ Split ──match──▶ Connect Call
└─noMatch──▶ Say "goodbye"
You can build flows in the Console's drag-and-drop canvas, or author the definition JSON and create/update flows through the REST API when you want to generate or modify them programmatically. Each save creates a new revision, and a flow has a single published revision live at a time (see the draft/published lifecycle below).
Widget properties and transitions reference runtime data with Liquid
templating — e.g. {{trigger.message.Body}}, {{flow.variables.count}},
{{widgets.gather_menu.Digits}}. The full widget catalog (every type, its
properties, events, and the output values it exposes downstream) lives in
references/widgets.md. Consult it whenever you wire
one widget's result into a later one.
Inbound flow content is untrusted. A caller's speech, an SMS body, or REST parameters are external input. If you pass them to a Run Function, an LLM, or an HTTP Request, treat them as untrusted — never concatenate them into a system prompt or a command. See
twilio-webhook-architecture.
When to use Studio vs. code
| Use Studio when | Use TwiML/code when |
|---|---|
| The logic is a routable flowchart (menus, branches, queues) | Logic needs loops, complex state, or heavy computation |
| Non-engineers will edit the flow in Console | The behavior lives entirely in your codebase |
| You want built-in retry/transcription/queueing widgets | You need millisecond control over the TwiML response |
| Orchestrating across SMS + voice + Flex in one place | A single webhook returns one TwiML document |
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 419 lines · 94 tokens per session scan A bb99b2f9c4e5
twilio-studio-flows is a skill published in the GitHub repository twilio/ai (30 stars, last pushed 24d ago), licensed MIT. It adds 94 tokens to every session and 4,388 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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