Kryspin Ziemski kziemski

Deploying TanStack Start Apps to Cloudflare Workers with GitHub Actions

Maybe you're a vibe coder, or you're a seasoned vet who's frustrated with Next and server components. Either way, I'll show you how to set up continuous deployment for a TanStack Start application to Cloudflare Workers using GitHub Actions (securely, of course).

Assumption:

You have a TanStack Start project initialized.
Package manager like pnpm or npm

Prereqs:

Deploying TanStack Start Apps to Cloudflare Workers with GitHub Actions

Maybe you're a vibe coder, or you're a seasoned vet who's frustrated with Next and server components. Either way, I'll show you how to set up continuous deployment for a TanStack Start application to Cloudflare Workers using GitHub Actions (securely, of course).

Assumption:

You have a TanStack Start project initialized.
Package manager like pnpm or npm

Prereqs:

Security Checklist (What can be done in CursorAI & software-level not infrastructure!)

Configuration Security

Detect secrets in code
Identify secrets committed to version control
Flag hardcoded credentials

Authentication & Authorization

Identify missing authentication checks
Detect improper authorization patterns

	// put this in src/pages/.well-known/appspecific/com.chrome.devtools.json.ts
	import type { APIRoute } from "astro"
	import { join } from "node:path"

	// https://chromium.googlesource.com/devtools/devtools-frontend/+/main/docs/ecosystem/automatic_workspace_folders.md
	export const GET: APIRoute = () => {
	return new Response(
	JSON.stringify({
	"workspace": {
	"root": join(import.meta.dirname, "../../../../../.."),

	# Project Policy

	This policy provides a single, authoritative, and machine-readable source of truth for AI coding agents and humans, ensuring that all work is governed by clear, unambiguous rules and workflows. It aims to eliminate ambiguity, reduce supervision needs, and facilitate automation while maintaining accountability and compliance with best practices.

	# 1. Introduction

	> Rationale: Sets the context, actors, and compliance requirements for the policy, ensuring all participants understand their roles and responsibilities.

	## 1.1 Actors

	import { randomBytes } from "node:crypto";
	import {
	copyFileSync,
	existsSync,
	mkdirSync,
	readdirSync,
	renameSync,
	rmSync,
	writeFileSync,
	} from "node:fs";

	// Update globs depending on your framework
	---
	name: tailwind_v4
	description: Guide for using Tailwind CSS v4 instead of v3.x
	globs: ["*/.{js,ts,jsx,tsx,mdx,css}"]
	tags:
	- tailwind
	- css
	---

	# train_grpo.py
	#
	# See https://github.com/willccbb/verifiers for ongoing developments
	#
	"""
	citation:

	@misc{brown2025grpodemo,
	title={Granular Format Rewards for Eliciting Mathematical Reasoning Capabilities in Small Language Models},
	author={Brown, William},

	"use client";

	import React from "react";
	import { View, StyleSheet, Animated, Easing, ViewStyle } from "react-native";

	const BASE_COLORS = {
	dark: { primary: "rgb(17, 17, 17)", secondary: "rgb(51, 51, 51)" },
	light: {
	primary: "rgb(250, 250, 250)",
	secondary: "rgb(205, 205, 205)",

	Begin by enclosing all thoughts within <thinking> tags, exploring multiple angles and approaches.
	Break down the solution into clear steps within <step> tags. Start with a 20-step budget, requesting more for complex problems if needed.
	Use <count> tags after each step to show the remaining budget. Stop when reaching 0.
	Continuously adjust your reasoning based on intermediate results and reflections, adapting your strategy as you progress.
	Regularly evaluate progress using <reflection> tags. Be critical and honest about your reasoning process.
	Assign a quality score between 0.0 and 1.0 using <reward> tags after each reflection. Use this to guide your approach:

	0.8+: Continue current approach
	0.5-0.7: Consider minor adjustments
	Below 0.5: Seriously consider backtracking and trying a different approach