I spent the last few months obsessed with a specific bottleneck: every time I start a new AI agent project, I waste the first few weeks on the same "foundational" plumbing.

Whether it is building lead research pipelines, setting up data extraction, or wrestling with .cursorrules to stop hallucinations, we are all rebuilding the same generic 80% over and over.

The AI ecosystem is currently fragmented across MCP servers for Claude, coding rules for Cursor, and production tools for the Vercel AI SDK. I wanted a "unified layer" where these capabilities are standardized, secure, and chainable.

So I built the Skene Cookbook. It is an open-source directory of 800+ AI skills and production-ready "Skill Chains" that you can install with one command.

GitHub: https://github.com/SkeneTechnologies/skene-cookbook

What is inside:

808 Standardized Skills: Hardened across 29 domains (SaaS, Marketing, security, and more).

Unified Support: Standardized patterns that work across Claude, Cursor, and Vercel.

Skill Chains: Pre-mapped logic for complex loops like churn prevention and viral referrals. You do not just get the blocks; you get the instructions on how to chain them together.

Audit & Security: Every skill has been audited for zero critical risks from Day 1.

To try it out:

npm install @skene/skills-directory

The "Skill Chains" are what I am most excited about. Instead of writing a referral system from scratch, you can deploy a chain: invite_system_audit -> dynamic_referral_generator -> attribution_tracking.

I have documented several of these "recipes" here: https://github.com/SkeneTechnologies/skene-cookbook/blob/mai...

I am making this MIT licensed because I think the "AI infrastructure tax" is slowing down the entire ecosystem. I’d love to hear your feedback on the architecture and what kind of chains you would want to see added next.

I will be around to answer any questions!