twilio-reliability-patterns

twilio-reliability-patterns is a skill for Claude Code, Codex from twilio/ai. It costs 72 tokens per session (2,533 once invoked), scanned A, original, MIT.

A guide to handling Twilio rate limits and temporary failures when sending messages or making calls at scale. It explains retries, throughput limits, delivery callbacks, and fallback paths.

In plain words
What is it for?
Use it to add exponential backoff with random delays, manage messages or calls per second, process status callbacks reliably, and design fallback behavior.
Why use it?
It prevents bursts of traffic and poorly timed retries from causing more failures, lost status updates, or overloaded services.

Skill for Claude CodeCodex

Part of the ai plugin — 57 skills shipped together

Install

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.

agentmods
npx agentmods add skills/twilio/ai/twilio-reliability-patterns
Any agent
npx skills add twilio/ai --skill twilio-reliability-patterns
Clone the repo
git clone --depth 1 https://github.com/twilio/ai

Made for: Claude Code, Codex.

Or install ai, the plugin that ships this one along with the rest of its 57 skills.

Wrote 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.

agentmods badge for twilio-reliability-patterns

README.md
[![agentmods](https://agentmods.dev/badge/skills/twilio/ai/twilio-reliability-patterns.svg)](https://agentmods.dev/skills/twilio/ai/twilio-reliability-patterns)
Your own site
<a href="https://agentmods.dev/skills/twilio/ai/twilio-reliability-patterns"><img src="https://agentmods.dev/badge/skills/twilio/ai/twilio-reliability-patterns.svg" alt="Measured on agentmods" height="20"></a>
Per session 72 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,533 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00072 $0.02533
Opus 5 $0.00036 $0.01267
Sonnet 5 $0.00014 $0.00507
Haiku 4.5 $0.00007 $0.00253

Measured 5d ago against content hash 0ca7d88af0b2, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

twilio-reliability-patterns 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 5d 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.

skills/twilio/twilio-reliability-patterns/SKILL.md · 291 lines

How it starts

The opening of the file, as written. The whole thing — 291 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Overview

Twilio enforces per-resource rate limits. At scale, 429 errors are expected behavior — not bugs. This skill teaches the patterns that prevent production failures: exponential backoff, throughput management, and resilient callback handling.

429 concurrency errors are not well documented — implement exponential backoff with ±10% jitter.


Prerequisites

  • A working Twilio integration (any product)
  • Understanding of your expected volume (messages/sec, calls/sec)
  • StatusCallback URLs configured — see twilio-messaging-services, twilio-sms-send-message

Key Patterns

1. Exponential Backoff with Jitter

When you receive a 429 (Too Many Requests), wait and retry. Naive fixed-interval retry creates thundering herds. Use exponential backoff with randomized jitter.

Python

import time, random, requests

def send_with_backoff(client, to, body, messaging_service_sid, max_retries=5):
    for attempt in range(max_retries):
        try:
            message = client.messages.create(
                to=to,
                body=body,
                messaging_service_sid=messaging_service_sid,
                status_callback="https://yourapp.com/status"
            )
            return message
        except Exception as e:
            if hasattr(e, 'status') and e.status == 429:
                # Exponential backoff: 100ms, 200ms, 400ms, 800ms, 1600ms
                base_delay = 0.1 * (2 ** attempt)
                # Add ±10% jitter to prevent thundering herd
                jitter = base_delay * 0.1 * (2 * random.random() - 1)
                delay = min(base_delay + jitter, 30)  # cap at 30 seconds
                time.sleep(delay)
            else:
                raise  # Non-429 errors: don't retry, investigate
    raise Exception(f"Failed after {max_retries} retries")

Node.js

async function sendWithBackoff(client, to, body, messagingServiceSid, maxRetries = 5) {
    for (let attempt = 0; attempt < maxRetries; attempt++) {
        try {
            return await client.messages.create({
                to,
                body,
                messagingServiceSid,
                statusCallback: "https://yourapp.com/status",
            });
        } catch (err) {
            if (err.status === 429) {
                // Exponential backoff: 100ms, 200ms, 400ms, 800ms, 1600ms
                const baseDelay = 100 * Math.pow(2, attempt);
                // Add ±10% jitter
                const jitter = baseDelay * 0.1 * (2 * Math.random() - 1);
                const delay = Math.min(baseDelay + jitter, 30000); // cap at 30s
                await new Promise(r => setTimeout(r, delay));
            } else {
                throw err; // Non-429: don't retry
            }
        }
    }
    throw new Error(`Failed after ${maxRetries} retries`);
}

Read the full file on GitHub · 291 lines

Files

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.

Changes

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.

  1. 5d ago First seen · 291 lines · 72 tokens per session scan A 0ca7d88af0b2

Subscribe to this mod's changes

twilio-reliability-patterns is a skill published in the GitHub repository twilio/ai (30 stars, last pushed 21d ago), licensed MIT. It adds 72 tokens to every session and 2,533 once invoked, about $0.0004 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.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

brainstorming

You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.

obra/superpowers · 37 tokens

auto-perf-optimize

Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.

microsoft/vscode · 62 tokens

chat-perf

Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.

microsoft/vscode · 51 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens