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-agent-connectgit 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-agent-connect)<a href="https://agentmods.dev/skills/twilio/ai/twilio-agent-connect"><img src="https://agentmods.dev/badge/skills/twilio/ai/twilio-agent-connect/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/twilio/ai/twilio-agent-connect"><img src="https://agentmods.dev/badge/skills/twilio/ai/twilio-agent-connect.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00000 | $0.03555 |
| Opus 5 | $0.00000 | $0.01777 |
| Sonnet 5 | $0.00000 | $0.00711 |
| Haiku 4.5 | $0.00000 | $0.00356 |
Grade A, and why
twilio-agent-connect 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 9d 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 — 534 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Twilio Agent Connect
Overview
Twilio Agent Connect (TAC) is a Python and TypeScript SDK that integrates third-party LLM agentic applications with Twilio's communication technologies. TAC provides middleware for identity resolution, memory/context management (via Conversation Memory), conversation orchestration (via Conversation Orchestrator), and multi-channel handling (Voice, SMS, RCS, WhatsApp, Chat).
Key Architecture Principle: TAC is not an agent runtime itself—it's middleware that enables existing LLM applications (OpenAI Agents SDK, Bedrock, LangChain, Microsoft Foundry, etc.) to leverage Twilio Conversations services.
Product Context
Core Twilio Conversations Services
TAC integrates with three core Twilio Conversations services:
-
Conversation Memory (Memory Store) - Persistent user context and memory management
- Profile storage with traits and attributes
- Observation and summary storage
- Session history with full conversation context
- Identity resolution (profile lookup by phone/email)
-
Conversation Orchestrator - Multi-channel conversation lifecycle management
- Unified conversation API across all channels
- Participant management
- Communication routing
- Conversation grouping and configuration
-
Enterprise Knowledge - Knowledge base integration
- Semantic search across knowledge bases
- RAG (Retrieval-Augmented Generation) support
- Knowledge chunk retrieval with relevance scoring
Supported Channels
TAC provides built-in support for:
- Voice - ConversationRelay (WebSocket-based real-time voice)
- SMS - Text messaging
- RCS - Rich Communication Services
- WhatsApp - WhatsApp Business messaging
- Chat - Web chat integrations
All channels support both inbound (customer-initiated) and outbound (agent-initiated) conversations.
ConversationRelay-Only Mode
TAC supports a simplified "ConversationRelay-only" mode for getting started with voice conversations without requiring Conversation Orchestrator or Conversation Memory setup. This mode provides:
- TwiML generation
- WebSocket protocol handling
- Voice conversation lifecycle management
- Callback-based message processing
What ships with it
3 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.
- 9d ago First seen · 534 lines · 0 tokens per session scan A e826ab01ba4b
twilio-agent-connect is a skill published in the GitHub repository twilio/ai (30 stars, last pushed 25d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 3,555 tokens. 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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