Sentry Tanstack Start Sdk logo

Sentry Tanstack Start Sdk

Organization
getsentry
sentry-tanstack-start-sdk

Full Sentry SDK setup for TanStack Start React. Use when asked to "add Sentry to TanStack Start", "install @sentry/tanstackstart-react", or configure error monitoring, tracing, session replay, logs, or user feedback in a TanStack Start React app.

Overview

Publishergetsentry
Repositorysentry-for-ai
Skill namesentry-tanstack-start-sdk
Stars
269
Forks
34
Bundled files
6
LicenseApache-2.0
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.

  • 6 bundled files

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

  • Open source

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

Installation

Install the Sentry Tanstack Start Sdk 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/getsentry/sentry-for-ai/tree/main/skills-legacy/sentry-tanstack-start-sdk
  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/getsentry/sentry-for-ai.git /tmp/sentry-for-ai
mkdir -p .claude/skills
cp -r /tmp/sentry-for-ai/skills-legacy/sentry-tanstack-start-sdk .claude/skills/sentry-tanstack-start-sdk
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Sentry Tanstack Start 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 Sentry Tanstack Start 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 Sentry Tanstack Start 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.

All Skills > SDK Setup > TanStack Start React SDK

Sentry TanStack Start React SDK

Opinionated wizard that scans your TanStack Start React project and guides you through complete Sentry setup for browser and server runtimes.

Invoke This Skill When

  • User asks to "add Sentry to TanStack Start" or "set up Sentry" in a TanStack Start React app
  • User wants to install or configure @sentry/tanstackstart-react
  • User wants error monitoring, tracing, session replay, logs, or user feedback for TanStack Start React
  • User asks about sentryTanstackStart, wrapFetchWithSentry, instrument.server.mjs, or TanStack Start middleware instrumentation

Note: This SDK is currently alpha and documented as compatible with TanStack Start 1.0 RC. Always verify against docs.sentry.io/platforms/javascript/guides/tanstackstart-react/ before implementing.


Phase 1: Detect

Run these commands to understand the project before making any recommendations:

bash
# Detect TanStack Start / Router and existing Sentry
cat package.json | grep -E '"@tanstack/react-start"|"@tanstack/react-router"|"@sentry/tanstackstart-react"'

# Check if Sentry is already present
cat package.json | grep '"@sentry/'

# Detect key files used by the TanStack Start setup
ls src/router.tsx src/start.ts src/server.ts instrument.server.mjs vite.config.ts vite.config.js 2>/dev/null

# Check whether source map upload credentials are configured
cat .env .env.local .env.sentry-build-plugin 2>/dev/null | grep "SENTRY_AUTH_TOKEN"

# Detect deployment hints in scripts
cat package.json | grep -E '"dev"|"build"|"start"|NODE_OPTIONS|--import'

# Detect logging libraries
cat package.json | grep -E '"pino"|"winston"|"loglevel"'

# Detect companion backend directories
ls ../backend ../server ../api 2>/dev/null
cat ../go.mod ../requirements.txt ../Gemfile ../pom.xml 2>/dev/null | head -3

What to determine:

QuestionImpact
@tanstack/react-start present?Confirms this skill is the right setup path
@sentry/tanstackstart-react already installed?Skip install and go to feature tuning
src/router.tsx exists?Client-side Sentry.init placement
src/start.ts exists?Global middleware setup for server-side errors
src/server.ts exists?Server entry instrumentation placement
instrument.server.mjs exists?Runtime startup instrumentation path
vite.config.ts exists?Add sentryTanstackStart plugin and source maps
SENTRY_AUTH_TOKEN configured?Source map upload readiness
Backend directory found?Trigger Phase 4 cross-link suggestion

Phase 2: Recommend

Present a concrete recommendation based on what you found. Do not ask open-ended questions — lead with a proposal:

Recommended (core coverage):

  • ✅ Error Monitoring — always; captures unhandled client and server errors
  • ✅ Tracing — high-value for request and route timing across browser and server
  • ✅ Session Replay — recommended for user-facing apps

Optional (enhanced observability):

  • ⚡ Logs — recommend when structured log search and log-to-trace correlation are needed
  • ⚡ User Feedback — recommend when product teams want in-app issue reports

Recommendation logic:

FeatureRecommend when...
Error MonitoringAlways — non-negotiable baseline
TracingUsually yes for TanStack Start; route + fetch instrumentation gives immediate value
Session ReplayUser-facing app, login flows, checkout flows, or hard-to-reproduce UX bugs
LogsExisting logging strategy, support workflow, or trace/log correlation needs
User FeedbackTeam wants direct user reports without leaving the app

Propose: "I recommend Error Monitoring + Tracing + Session Replay. Want me to also enable Logs and User Feedback?"


Phase 3: Guide

Install

bash
npm install @sentry/tanstackstart-react --save

Configure Client-Side Sentry in src/router.tsx

Initialize Sentry inside the router factory and gate it to the browser:

tsx
import * as Sentry from "@sentry/tanstackstart-react";
import { createRouter } from "@tanstack/react-router";

export const getRouter = () => {
  const router = createRouter();

  if (!router.isServer) {
    Sentry.init({
      dsn: "___PUBLIC_DSN___",
      dataCollection: {
        // userInfo: false,
        // httpBodies: [],
      },

      integrations: [
        Sentry.tanstackRouterBrowserTracingIntegration(router),
        Sentry.replayIntegration(),
        Sentry.feedbackIntegration({
          colorScheme: "system",
        }),
      ],

      enableLogs: true,
      tracesSampleRate: 1.0,
      replaysSessionSampleRate: 0.1,
      replaysOnErrorSampleRate: 1.0,
    });
  }

  return router;
};

Configure Server-Side Sentry in instrument.server.mjs

Create instrument.server.mjs in project root:

javascript
import * as Sentry from "@sentry/tanstackstart-react";

Sentry.init({
  dsn: "___PUBLIC_DSN___",
  dataCollection: {
    // To disable sending user data and HTTP bodies, uncomment the lines below. For more info visit:
    // https://docs.sentry.io/platforms/javascript/guides/tanstackstart-react/configuration/options/#dataCollection
    // userInfo: false,
    // httpBodies: [],
  },
  enableLogs: true,
  tracesSampleRate: 1.0,
});

Configure Vite Plugin in vite.config.ts

sentryTanstackStart should be the last plugin:

typescript
import { defineConfig } from "vite";
import { sentryTanstackStart } from "@sentry/tanstackstart-react/vite";
import { tanstackStart } from "@tanstack/react-start/plugin/vite";

export default defineConfig({
  plugins: [
    tanstackStart(),
    sentryTanstackStart({
      org: "___ORG_SLUG___",
      project: "___PROJECT_SLUG___",
      authToken: process.env.SENTRY_AUTH_TOKEN,
    }),
  ],
});

If the token is stored in .env, load it with loadEnv in the Vite config before passing it to the plugin.

Instrument Server Entry Point in src/server.ts

Wrap the fetch handler with wrapFetchWithSentry:

typescript
import { wrapFetchWithSentry } from "@sentry/tanstackstart-react";
import handler, { createServerEntry } from "@tanstack/react-start/server-entry";

export default createServerEntry(
  wrapFetchWithSentry({
    fetch(request: Request) {
      return handler.fetch(request);
    },
  }),
);

Add Global Server Middleware in src/start.ts

These middleware capture server-side request and function errors:

tsx
import {
  sentryGlobalFunctionMiddleware,
  sentryGlobalRequestMiddleware,
} from "@sentry/tanstackstart-react";
import { createStart } from "@tanstack/react-start";

export const startInstance = createStart(() => {
  return {
    requestMiddleware: [sentryGlobalRequestMiddleware],
    functionMiddleware: [sentryGlobalFunctionMiddleware],
  };
});

Sentry middleware should be first in each array.

Runtime Startup Patterns

Choose one runtime method:

Runtime patternUse when...Notes
--import flagYou can control Node startup flagsPreferred for production monitoring
Direct import in src/server.tsHost restricts startup flags (for example serverless hosts)Limits instrumentation to native Node APIs

--import examples:

json
{
  "scripts": {
    "dev": "NODE_OPTIONS='--import ./instrument.server.mjs' vite dev --port 3000",
    "build": "vite build && cp instrument.server.mjs .output/server",
    "start": "node --import ./.output/server/instrument.server.mjs .output/server/index.mjs"
  }
}

Direct import fallback (top of src/server.ts):

typescript
import "../instrument.server.mjs";

For Each Agreed Feature

Walk through features one at a time. Load the reference file, follow steps exactly, and verify before moving on:

FeatureReferenceLoad when...
Error Monitoring${SKILL_ROOT}/references/error-monitoring.mdAlways
Tracing${SKILL_ROOT}/references/tracing.mdRoute/API performance visibility needed
Session Replay${SKILL_ROOT}/references/session-replay.mdUser-facing app
Logs${SKILL_ROOT}/references/logging.mdStructured logs and correlation needed
User Feedback${SKILL_ROOT}/references/user-feedback.mdIn-app feedback collection needed
TanStack Start Features${SKILL_ROOT}/references/tanstackstart-features.mdServer entry, Vite plugin, source maps, runtime startup

For each feature: Read ${SKILL_ROOT}/references/<feature>.md, follow steps exactly, verify it works.


Configuration Reference

Key Sentry.init() Options

OptionTypeDefaultNotes
dsnstring—Required; SDK is disabled when empty
dataCollectionobjectconservative unless setFine-grained control over auto-collected categories (userInfo, cookies, httpHeaders, httpBodies, queryParams, genAI). When omitted, the SDK falls back to sendDefaultPii (default false). Passing the object — even {} — flips unset categories to their permissive defaults; opt out per category.
integrationsIntegration[]SDK defaultsInclude TanStack Router tracing, replay, feedback as needed
enableLogsbooleanfalseEnables Sentry.logger.* APIs
tracesSampleRatenumber—1.0 in development, lower in production
replaysSessionSampleRatenumber—Fraction of all sessions recorded
replaysOnErrorSampleRatenumber—Fraction of error sessions recorded
tunnelstring—Optional ad-blocker bypass endpoint
debugbooleanfalseSDK diagnostic logging

TanStack Start-Specific APIs

APIPurpose
tanstackRouterBrowserTracingIntegration(router)Browser navigation tracing
wrapFetchWithSentry(...)Server request tracing + error capture on fetch handler
sentryGlobalRequestMiddlewareCaptures request-level server errors
sentryGlobalFunctionMiddlewareCaptures server function errors
sentryTanstackStart({...})Vite plugin for source maps and middleware instrumentation

Verification

Trigger test events to confirm Sentry receives data.

Issues Test (Frontend)

tsx
<button
  type="button"
  onClick={() => {
    throw new Error("Sentry Test Error");
  }}
>
  Break the world
</button>

Tracing Test (Frontend + API Route)

tsx
<button
  type="button"
  onClick={async () => {
    await Sentry.startSpan({ name: "Example Frontend Span", op: "test" }, async () => {
      const res = await fetch("/api/sentry-example");
      if (!res.ok) {
        throw new Error("Sentry Example Frontend Error");
      }
    });
  }}
>
  Break the world
</button>

Logs Test

javascript
Sentry.logger.info("User example action completed");
Sentry.logger.warn("Slow operation detected", { operation: "data_fetch", duration: 3500 });
Sentry.logger.error("Validation failed", { field: "email", reason: "Invalid email" });

Confirm in Sentry:

  • Issues: frontend/server errors appear
  • Traces: browser and server spans appear
  • Replays: session replay appears when enabled
  • Logs: log lines appear when enableLogs: true
  • User Feedback: submissions appear when feedback integration is enabled

Phase 4: Cross-Link

After completing TanStack Start setup, check whether a companion backend exists without Sentry:

bash
ls ../backend ../server ../api ../go ../python 2>/dev/null
cat ../go.mod ../requirements.txt ../pyproject.toml ../Gemfile ../pom.xml 2>/dev/null | head -5

If a backend exists without Sentry configured, suggest the matching skill:

Backend detectedSuggest skill
Go (go.mod)sentry-go-sdk
Python (requirements.txt, pyproject.toml)sentry-python-sdk
Ruby (Gemfile)sentry-ruby-sdk
Java (pom.xml, build.gradle)Use @sentry/java docs
Node.js backend servicessentry-node-sdk

Troubleshooting

IssueSolution
Events not appearingSet debug: true, verify DSN, and ensure client/server init files both run
No server tracesConfirm src/server.ts uses wrapFetchWithSentry and runtime loads instrument.server.mjs
Server errors missing from route handlersEnsure sentryGlobalRequestMiddleware and sentryGlobalFunctionMiddleware are first in arrays
Source maps not resolvingVerify SENTRY_AUTH_TOKEN, org, and project in sentryTanstackStart config
SENTRY_AUTH_TOKEN undefined in Vite configUse loadEnv(mode, process.cwd(), "") or .env.sentry-build-plugin
Replay not recordingEnsure replayIntegration() is in integrations and sample rates are non-zero
Feedback widget not visibleConfirm feedbackIntegration() is configured and check CSS z-index conflicts
Logs missing in SentrySet enableLogs: true and use Sentry.logger.* APIs
Direct-import setup misses library spansPrefer --import startup when possible; direct import supports native Node instrumentation only
SSR rendering exceptions not auto-capturedCapture manually with Sentry.captureException in error boundaries / fallback handlers

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 Tanstack Start Sdk AI skill do?

Full Sentry SDK setup for TanStack Start React. Use when asked to "add Sentry to TanStack Start", "install @sentry/tanstackstart-react", or configure error monitoring, tracing, session replay, logs, or user feedback in a TanStack Start React app.

Why use Sentry Tanstack Start Sdk on TypingMind?

Because you install it once and use it with any model. Sentry Tanstack Start 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 Sentry Tanstack Start Sdk in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/getsentry/sentry-for-ai/tree/main/skills-legacy/sentry-tanstack-start-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 Sentry Tanstack Start 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 Sentry Tanstack Start Sdk?

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

Is the Sentry Tanstack Start Sdk AI skill free?

Yes. It is published on GitHub by getsentry under the Apache-2.0 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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