Rivet Sdk

Organization

zoom

rivet-sdk

Zoom Rivet SDK for JavaScript/TypeScript server-side integrations. Use for auth handling, webhook event consumers, API endpoint wrappers, multi-module app composition, and AWS Lambda receiver patterns.

Overview

Publisher	zoom
Repository	`skills`
Skill name	`rivet-sdk`
Stars	78
Forks	16
Bundled files	12
License	MIT
Links	Skill source Repository

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
12 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by zoom on GitHub. Read the source before you install it.

Installation

Install the Rivet Sdk AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/zoom/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/rivet-sdk .claude/skills/rivet-sdk

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Rivet Sdk in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Rivet Sdk on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Rivet Sdk is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Zoom Rivet SDK

Implementation guidance for Zoom Rivet (JavaScript/TypeScript) as a server-side framework for:

OAuth and token handling
Webhook event consumption
Typed REST API endpoint wrappers
Multi-module server composition

Current npm package verified on 2026-07-10: @zoom/rivet@0.4.0.

Official docs:

https://developers.zoom.us/docs/rivet/
https://developers.zoom.us/docs/rivet/javascript/
https://zoom.github.io/rivet-javascript/

Reference samples:

https://github.com/zoom/rivet-javascript-sample
https://github.com/zoom/isv-rivet-starter
https://github.com/zoom/Rivet-Server-Sample
https://github.com/zoom/rivet-javascript

Routing Guardrail

Rivet SDK is a Node.js framework that bundles Zoom auth handling, webhook receivers, and typed API wrappers.
Rivet is recommended for faster server-side scaffolding, but it is not mandatory.
At planning start, confirm preference:
Do you want Rivet SDK, or direct OAuth + REST without Rivet?
Use Rivet when the user wants a Node.js server that combines Zoom auth + webhooks + API calls with minimal glue code.
If the user only needs direct API calls from an existing backend, chain with ../rest-api/SKILL.md.
If the user is focused on Zoom Team Chat app cards/commands behavior, chain with ../team-chat/SKILL.md.
If the user needs SDK embed (Meeting SDK/Video SDK client runtime), route to ../meeting-sdk/SKILL.md or ../video-sdk/SKILL.md.

Quick Links

Start here:

concepts/architecture-and-lifecycle.md
scenarios/high-level-scenarios.md
examples/getting-started-pattern.md
examples/multi-client-pattern.md
references/rivet-reference-map.md
references/versioning-and-compatibility.md
references/samples-validation.md
references/source-map.md
references/environment-variables.md
troubleshooting/common-issues.md
RUNBOOK.md
rivet-sdk.md

Common Lifecycle Pattern

Choose modules and auth model per module (Client Credentials, User OAuth, S2S OAuth, Video SDK JWT).
Instantiate client(s) with credentials, webhook secret, and per-module port.
Register event handlers (webEventConsumer.event(...) or shortcuts).
Implement API calls through client.endpoints.*.
Start receiver(s) and expose webhook endpoint(s) (/zoom/events) to Zoom.
Persist tokens/state for OAuth workloads and enforce signature verification.
Monitor module-specific failures and rotate secrets/version with changelog cadence.

Need to create the Zoom app(s) first? Use Marketplace app management to create or validate the required General, S2S, webhook/event, or Video SDK app credentials before wiring Rivet modules.

High-Level Scenarios

Team Chat slash-command bot + Team Chat data API enrichment.
Multi-module backend (Users + Meetings + Team Chat + Phone + Commerce) sharing one process.
Marketplace automation module paired with the Marketplace app templates in this repository.
Video SDK telemetry backend using videosdk module event stream + API surfaces.
ISV orchestration layer with tenant-aware token storage and per-module webhooks.
AWS Lambda webhook processor with Rivet AwsLambdaReceiver.

See scenarios/high-level-scenarios.md for details.

Chaining

OAuth architecture and grant selection: ../oauth/SKILL.md
API endpoint semantics and request payload details: ../rest-api/SKILL.md
Team Chat app cards, command and bot UX: ../team-chat/SKILL.md
Video SDK API-specific behavior and BYOS context: ../video-sdk/SKILL.md

Environment Variables

See references/environment-variables.md for standardized .env keys and where to find each value.

Operations

RUNBOOK.md - 5-minute preflight and debugging checklist.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Rivet Sdk AI skill do?

Why use Rivet Sdk on TypingMind?

Because you install it once and use it with any model. Rivet Sdk is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Rivet Sdk in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/zoom/skills/tree/main/skills/rivet-sdk. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Rivet Sdk?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Rivet Sdk?

As many as you like. As long as a model supports skills, you can use Rivet Sdk with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Rivet Sdk AI skill free?

Yes. It is published on GitHub by zoom under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Finishing A Development Branch

obra

CommunityPopular

Use when implementation is complete, all tests pass, and you need to decide how to integrate the work

Receiving Code Review

obra

CommunityPopular

Use when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative…

Requesting Code Review

obra

CommunityPopular

Use when completing tasks, implementing major features, or before merging to verify work meets requirements

Systematic Debugging

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

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Zoom Rivet SDK

Routing Guardrail

Quick Links

Common Lifecycle Pattern

High-Level Scenarios

Chaining

Environment Variables

Operations

Bundled files

Frequently asked questions

Related AI Skills

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