StackScope – Tech Stack Intelligence for Product Launches

TL;DR

TL;DR: StackScope analyses 43,000+ product launches from Product Hunt, Hacker News, and PeerPush to reveal what frameworks, hosting, AI signals, and security headers indie builders actually ship with.

Source and Accuracy Notes

• Project page: stackscope.dev
• HN launch thread: news.ycombinator.com/item?id=48505364
• Source last checked: 2026-06-16

What Is StackScope?

StackScope is a tech stack intelligence platform that crawls and analyses new product launches across major indie launch platforms. It answers the question every builder asks before shipping: “What are successful launches actually using?”

The platform tracks 43,053 launches from three key sources:

• Product Hunt – the mainstream launch platform
• Hacker News – Show HN posts and technical launches
• PeerPush – emerging launch community

Each launch gets analysed for its underlying infrastructure: hosting provider, frontend framework, analytics tools, security headers, DNS configuration, email setup, and increasingly important – AI signals (whether the site appears AI-generated, how it handles AI crawlers, llms.txt adoption).

How It Works

Daily Automated Analysis

StackScope runs daily crawls of new launches, extracting technical fingerprints without requiring any setup from the launchers themselves. The system detects:

• Hosting & CDN – Cloudflare (39% adoption), Vercel, AWS, Hetzner
• Frameworks – React (36%), Next.js (35%), Tailwind CSS (56%)
• Analytics – Google Analytics (40%), Google Search Console (61%)
• Security – HSTS headers (62%), HTTP/3 protocol (40%)
• AI signals – AI-generated content patterns, llms.txt presence, bot blocking rules

StackScope Score

Each launch receives a composite score (0-10) based on technical completeness, security posture, and modern best practices. Today’s standout example: SpendKeep scored 10.0 with privacy-first personal finance features.

The scoring helps identify which launches are built on solid foundations versus quick-and-dirty deploys.

Key Features

1. Technology Directory

Browse 4,967 unique technologies grouped by category:

• Analytics platforms
• Hosting providers
• Payment processors
• AI tools
• CSS frameworks
• Meta-frameworks

2. Trend Analysis

Track technology adoption over time. Recent insights include:

• 1,307 launches block AI bots but still publish llms.txt – the contradiction nobody planned for
• 19% of launches show strong AI generation patterns – AI-built sites are becoming visible
• 1,386,047 total tech detections across all analysed launches

3. AI Stance Tracking

StackScope monitors how new launches handle AI crawlers:

• Which sites block GPTBot, ClaudeBot, PerplexityBot
• Who publishes llms.txt for AI consumption
• The gap between blocking bots and providing AI-friendly documentation

4. Launch Readiness Check

Submit your own site to get a technical audit before launching. The check covers:

• Security headers (HSTS, CSP, X-Frame-Options)
• Performance signals (HTTP/3, CDN usage)
• SEO basics (Search Console, sitemaps)
• AI crawler handling

Practical Evaluation Checklist

When researching your next launch stack, use StackScope to answer:

Before choosing hosting:

• What CDN do 39% of successful launches use? (Answer: Cloudflare)
• Which hosting providers dominate in your category?

Before picking a framework:

• Is Next.js (35%) actually the default for meta-frameworks?
• How does Tailwind CSS adoption (56%) compare to other CSS approaches?

Before launch day:

• What security headers do 62% of launches implement? (HSTS)
• Should you block AI crawlers or publish llms.txt? (See the 1,307-launch contradiction)

After launch:

• How does your StackScope score compare to similar launches?
• What technologies are trending upward this month?

Deeper Analysis

The AI-Built Site Signal

StackScope detects patterns that suggest AI-generated websites. This matters because:

• 19% of new launches show strong AI generation patterns
• Investors and users are becoming skeptical of AI-slop sites
• Transparent AI use (with human oversight) vs. hidden AI generation affects trust

The llms.txt Paradox

One of StackScope’s most interesting findings: 1,307 launches block AI crawlers in robots.txt but still publish llms.txt files. This creates a contradictory signal – “don’t crawl me, but here’s documentation for AI systems.”

This suggests builders are uncertain about AI crawler strategy. StackScope’s data helps you see what the majority is doing before you decide your own stance.

Security Header Adoption

The 62% HSTS adoption rate shows security is becoming table stakes for indie launches. But StackScope also tracks:

• Content Security Policy (CSP) implementation
• X-Frame-Options for clickjacking protection
• Referrer-Policy settings

If you’re launching without these, you’re in the minority – and potentially exposing users to risks.

Security Notes

StackScope itself is a read-only analysis platform. It doesn’t require authentication to browse launches, and submitting your own site for analysis is non-invasive (it just crawls your public pages like any search engine bot).

Privacy considerations:

• StackScope stores technical fingerprints, not user data
• No login required for browsing
• Site submissions are public (your launch URL becomes part of the directory)

For your own launches:

• Use the Launch Readiness Check to catch missing security headers
• Review your AI crawler stance intentionally (block, allow, or conditional)
• Don’t treat llms.txt as a checkbox – decide if you actually want AI systems consuming your content

FAQ

Q: Is StackScope free to use? A: Browsing the directory and viewing launch analyses is free. The site doesn’t show pricing tiers in the main navigation, suggesting a freemium model or upcoming paid features.

Q: How often is the data updated? A: StackScope runs daily analysis of new launches from Product Hunt, Hacker News, and PeerPush. The “Today’s standout” section refreshes daily.

Q: Can I submit my own launch? A: Yes – there’s a “Check your own site” feature that analyses any URL and adds it to the directory.

Q: Does StackScope work for non-indie launches? A: The focus is on early-stage and indie launches from the three tracked platforms. Enterprise or B2B launches not posted to Product Hunt/HN/PeerPush won’t be captured automatically.

Q: How accurate is the AI-built site detection? A: StackScope looks for patterns (generic stock imagery, repetitive structure, specific framework combinations) rather than definitive proof. The 19% figure is a signal, not a diagnosis.

Q: Can I export the data? A: The site doesn’t prominently feature export options in the main navigation. API access or bulk exports may be available through paid tiers or direct contact.

Conclusion

StackScope fills a gap in the indie builder toolkit: empirical data on what successful launches actually ship with, rather than anecdotal Twitter threads or outdated “best stack” articles.

For builders about to launch, it’s a reality check. For researchers tracking web technology trends, it’s a longitudinal dataset. For anyone curious about the infrastructure behind the next wave of products, it’s a searchable directory of 43,000+ technical fingerprints.

The AI signals tracking is particularly timely – as AI-generated sites become more common, having data on adoption patterns, crawler handling, and transparency signals helps the community establish norms rather than guessing.

If you’re planning a launch in 2026, check your StackScope score before you hit “publish” on Product Hunt. You might be missing HSTS headers or publishing contradictory AI crawler rules.