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Sentry App Setup

OrganizationPopular
vellum-ai
sentry-app-setup

Create and configure a Sentry internal integration so the assistant can manage issues, alerts, and releases under its own identity

Overview

Publishervellum-ai
Repositoryvellum-assistant
Skill namesentry-app-setup
Stars
1.4K
Forks
208
Bundled files
4
LicenseMIT
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.

  • 4 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by vellum-ai on GitHub. Read the source before you install it.

Installation

Install the Sentry App Setup 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/vellum-ai/vellum-assistant/tree/main/skills/sentry-app-setup
  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/vellum-ai/vellum-assistant.git /tmp/vellum-assistant
mkdir -p .claude/skills
cp -r /tmp/vellum-assistant/skills/sentry-app-setup .claude/skills/sentry-app-setup
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Sentry App Setup 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 Sentry App Setup 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 Sentry App Setup 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.

Overview

Set up a Sentry internal integration so the assistant can interact with a Sentry organization — querying issues, resolving events, managing releases, and monitoring alerts as its own entity.

Internal integrations are scoped to a single organization. They don't require an OAuth flow — you get an auth token immediately after creation. Tokens don't expire automatically (but can be revoked manually).

Total manual effort: ~2 interactions — create the integration and grab the auth token.

Prerequisites

  • User must be an organization owner or manager in Sentry
  • User must be logged into Sentry in their browser

Setup Flow

Step 0: Check Existing Configuration

Before starting, check whether Sentry is already configured by running the check script:

bash
bun skills/sentry-app-setup/scripts/check-config.ts

The script outputs JSON: { "configured": boolean, "details": string }.

  • If configured is true — Sentry is already set up. Offer to verify the connection or reconfigure.
  • If configured is false — continue to Step 1.

Step 1: Create the Internal Integration

Direct the user to create a new internal integration:

Open https://sentry.io/settings/developer-settings/new-internal/ to create a new internal integration.

Guide them through the form:

FieldValue
NameThe assistant's name. This is how the integration appears in Sentry.
Webhook URLLeave blank (not needed for API-only usage)

Permissions — set these based on what the assistant needs. Recommended defaults:

ResourceAccess Level
Issue & EventRead
ProjectRead
OrganizationRead

Adjust permissions up or down based on the user's needs. The principle of least privilege applies — only request what you'll actually use. Add write access to Issue & Event or Project if the assistant needs to resolve issues or manage releases.

Click Save Changes when done. The integration is automatically installed on the organization.

Step 2: Collect the Auth Token

After saving, Sentry displays the integration's details page. An auth token is automatically generated.

Tell the user: on the integration details page, find the Tokens section and copy the auth token.

Then run the store script to securely collect and store the token:

bash
bun skills/sentry-app-setup/scripts/store-token.ts

The script opens a secure credential prompt in the user's app, stores the token in the encrypted vault with the correct injection templates, and exits. No further action needed — if it exits 0, the token is stored. Exit code 130 means the user cancelled the prompt — nothing was stored; that's a valid choice, not an error, so ask whether they'd like to try again rather than treating it as a failure. Any other non-zero exit is a real failure.

Step 3: Collect the Organization Slug

The org slug is needed for API calls. Ask the user for it — it's visible in their Sentry URL as sentry.io/organizations/{slug}/.

Remember the org slug for future API calls.

Step 4: Verify

After storing the token, verify the connection:

bash
curl -s https://sentry.io/api/0/organizations/{org_slug}/ \
  -H "Content-Type: application/json"

Run with network_mode: "proxied" and the sentry credential. A successful response returns the organization's details.

If the response returns a 401, the token is invalid or revoked. If 403, the integration doesn't have org:read permission.

Step 5: Set the Integration Logo (Optional)

Sentry supports uploading a logo for internal integrations through the web UI (not via API).

Direct the user:

Go to Settings > Developer Settings, find your integration, and upload a logo.

Logo requirements: PNG, 256×256 to 1024×1024, transparent background (unless the logo fills the entire space).

Small Icon requirements (optional, separate upload): PNG, must use only black with an alpha channel — no colors, no white fill. Sentry rejects icons that use any color other than black.

Step 6: Report Success

Summarize with the completed checklist:

"Setup complete! ✅ Internal integration created ✅ Auth token configured ✅ Connection verified {logo_line}

Connected: {integration_name} in {org_slug} Permissions: {list the configured permission levels} Token: does not expire (can be revoked in Settings > Developer Settings)"

For {logo_line}:

  • If logo was uploaded: ✅ Logo uploaded
  • If skipped: ⬜ Logo — upload anytime in Settings > Developer Settings

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 Sentry App Setup AI skill do?

Create and configure a Sentry internal integration so the assistant can manage issues, alerts, and releases under its own identity

Why use Sentry App Setup on TypingMind?

Because you install it once and use it with any model. Sentry App Setup 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 Sentry App Setup in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/vellum-ai/vellum-assistant/tree/main/skills/sentry-app-setup. 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 Sentry App Setup?

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 Sentry App Setup?

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

Is the Sentry App Setup AI skill free?

Yes. It is published on GitHub by vellum-ai 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.

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