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Rails Webhooks

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marckohlbrugge
rails-webhooks

Build and review Rails webhook systems with safe delivery, retries, observability, and tenant-aware security controls. Use when adding webhook endpoints, outbound deliveries, retry logic, or webhook admin tooling.

Overview

Publishermarckohlbrugge
Repository37signals-skills
Skill namerails-webhooks
Stars
724
Forks
56
Bundled files
Instructions only
Links
  • 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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by marckohlbrugge on GitHub. Read the source before you install it.

Installation

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

1

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.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/marckohlbrugge/37signals-skills/tree/main/skills/rails-webhooks
  4. 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.
2

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/marckohlbrugge/37signals-skills.git /tmp/37signals-skills
mkdir -p .claude/skills
cp -r /tmp/37signals-skills/skills/rails-webhooks .claude/skills/rails-webhooks
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Rails Webhooks 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 Rails Webhooks 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 Rails Webhooks 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.

Rails Webhooks

Use for outbound/inbound webhook architecture and reliability. Modeled on Fizzy's event-driven webhook pipeline (with Campfire's simpler bot webhooks as contrast).

Delivery Model (outbox pattern)

  • Domain events enqueue one dispatch job; the dispatch job fans out, creating one persisted Delivery row per webhook, each with a state enum (pending in_progress completed errored — string-backed via index_by(&:itself)).
  • Each delivery row auto-enqueues its own send via after_create_commit :deliver_later — persist first, deliver second, so state survives crashes and retries.
  • Fan-out is crash-safe with ActiveJob::Continuable: cursor over matching webhooks (find_each(start: step.cursor) + step.advance!) so a mid-batch crash resumes, not restarts.
  • Record request metadata (headers, payload) and response (status, body) on the delivery row for audit/debugging. Cap stored/streamed response bodies (~100KB) with a running byte count.
  • Use a dedicated webhooks queue so slow destinations can't starve other work.

Failure Classification (the key distinction)

  • Expected destination failures (timeout, TLS, DNS, connection refused, HTTP 4xx/5xx): rescue, mark delivery completed with a symbolic error (response: { error: :connection_timeout }). The delivery ran; the destination failed. Do not retry the job.
  • Unexpected exceptions (our bug): mark errored!, re-raise so ActiveJob retries.
  • This split keeps retry behavior, dashboards, and delinquency tracking honest.

Delinquency Circuit Breaker

  • Track consecutive failures + first_failure_at per webhook; auto-deactivate after N failures spanning a minimum window (Fizzy: 10 failures over 1+ hour).
  • Reset the counter on success.
  • Surface inactive state in the UI with a manual reactivation endpoint (resource :activation).

Security Baseline

  • Treat webhook URLs as untrusted input; apply full SSRF protections (resolve + validate IP, block private ranges, pin IP, re-validate per redirect — see rails-security-multitenancy).
  • Revalidate destination at send time, not just on create.
  • Destination URL is immutable after create — updates permit name/subscriptions only. Retargeting requires a new webhook (and new secret).
  • Sign payloads: HMAC signature header + timestamp header.
  • Whitelist subscribable events at the model layer: normalizes :subscribed_actions, with: ->(v) { Array.wrap(v).map(&:to_s).uniq & PERMITTED_ACTIONS }.
  • Require admin-level auth for webhook management endpoints.

Integration Adapters

  • One delivery pipeline can serve multiple destination types: detect by URL pattern (for_slack?, for_campfire?), then vary content type, payload format (JSON/form/HTML), and rendering template per destination. Don't fork the delivery code per integration.
  • Render payload URLs with tenant-correct script_name so links in payloads work.

Inbound Webhooks (receiving)

  • Verify the signature first (construct_event-style), then re-fetch canonical state from the provider's API instead of trusting payload content or ordering.
  • For chat-bot style callbacks: gate what responses can do by content type (only text/plain/text/html become replies), and prevent loops — never trigger a bot from its own messages.

Tenant Safety

  • Keep webhook records and delivery queries tenant-scoped.
  • Ensure event fan-out cannot leak cross-tenant data.

Operational Hygiene

  • Recurring cleanup of old delivery records by retention policy (e.g. every 4 hours, delete_all on a stale scope).
  • Surface delivery status/history in the webhook admin UI.
  • Emit useful logs/metrics for success rate, retries, and latency.

Red Flags

  • Fire-and-forget delivery with no persisted audit trail.
  • Retrying destination failures the same way as code errors.
  • Mutable webhook destination URLs.
  • No circuit breaker — hammering dead endpoints forever.
  • Unbounded reads of destination responses.
  • No tenant scoping in delivery creation/lookup.
  • No backpressure or queue isolation for high-volume events.

Frequently asked questions

What does the Rails Webhooks AI skill do?

Build and review Rails webhook systems with safe delivery, retries, observability, and tenant-aware security controls. Use when adding webhook endpoints, outbound deliveries, retry logic, or webhook admin tooling.

Why use Rails Webhooks on TypingMind?

Because you install it once and use it with any model. Rails Webhooks 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 Rails Webhooks in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/marckohlbrugge/37signals-skills/tree/main/skills/rails-webhooks. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Rails Webhooks?

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 Rails Webhooks?

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

Is the Rails Webhooks AI skill free?

It is published on GitHub by marckohlbrugge. Check the repository for licensing terms. 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.

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