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A growth-hacking skill library for Claude hits 760 stars in 4 days

Enso.bot's curated directory spans 14 GTM disciplines (SEO/GEO/AEO, CRO, lifecycle email, paid media, RevOps, PLG) packaged as Claude/ChatGPT/Manus.

Enterprise DNA |
A growth-hacking skill library for Claude hits 760 stars in 4 days

AI Pulse · Under the Radar

The play

Pull the growth-hacking skill library, compare its GEO and AEO patterns to yours, and adopt anything missing from your marketing stack.

A developer named mikiarlo3 just dropped a GitHub repository that collected 760 stars in four days. It’s a curated list of growth-hacking prompts and skills designed to plug straight into Claude, ChatGPT, or Manus. The library covers 14 go-to-market disciplines: SEO, GEO (generative engine optimisation), AEO (answer engine optimisation), conversion rate optimisation, lifecycle email, paid media, revenue operations, and product-led growth.

What makes this interesting is the packaging. Instead of vague prompt templates, these are structured as reusable skills you can wire into an AI agent and let it run. If you’re already automating parts of your marketing stack, this is the kind of library that slots in without rewriting your workflow. The GEO and AEO patterns are particularly worth a look if you’re trying to get your content surfacing in AI-generated answers, not just traditional search results. That’s a gap most companies haven’t closed yet.

The repo lives at the original directory and updates regularly. It’s open, so you can fork it, adapt the prompts to your own voice, and test what actually moves the needle in your funnel. The disciplines it covers map cleanly to the kinds of tasks we build into systems like the Omni Command Centre, where marketing automation, lead scoring, and content optimisation run as connected workflows rather than scattered scripts.

If your growth team is already experimenting with AI tooling, this is a low-friction way to expand what those tools can do. If you’re not automating yet, it’s a clear signal that the bar for entry keeps dropping. The skills are free, the infrastructure to run them is commodity, and the only real question is whether you’re set up to test and iterate fast enough to find what works.

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