I was wasting 14,287 tokens just correcting AI jargon. I built a "Master Teacher" skill to kill the surface-level loop.
Does anyone else feel like they’re babysitting their AI?
I use ChatGPT, Claude, Gemini for 6+ hours a day to learn new stacks. The biggest frustration isn't that the AI is "dumb", it’s that it’s too "smart." It assumes I already have a PhD in whatever I’m asking about. It throws high-level jargon at me, and when I ask it to simplify, it gets too shallow.
I spent weeks refining a "Master Teacher" logic to break this cycle. I call it Marrow.
The Logic: It’s a structural re-tuning that forces the AI into a specific pedagogical loop:
- Zero Knowledge Assumption: It never uses a technical term without explaining it from the ground up first.
- Marrow Identification: It automatically scans your question for the "Marrow"—the 20% of concepts that drive 80% of the meaning.
- Iterative Chunking: It explains 2-3 concepts deeply, then stops and asks if you're ready to proceed. No more "wall of text" skimming.
The Difference (Binary Example):
Normal AI: Binary is a number system that uses only two digits: 0 and 1.
Marrow: Binary is a way of representing information using only two possible values: 0 and 1.
I've open-sourced the whole thing. It’s MIT licensed and works as a one-liner for Cursor, Windsurf, and Cline.
IDE Install: npx skills add CodePandaaAI/marrow
Prompt File Link: https://github.com/CodePandaaAI/marrow/releases/download/marrow_v1.0.0/SKILL.md
Repo/Source: https://github.com/CodePandaaAI/marrow
I’m not selling anything, I just want to know if this logic works for your specific workflow. If you use it, let me know where it hits or misses. 🦴🚀
