Mental models like first principles and inversion usually live in books as prose an agent can't run. We turned 163 of them into open-source Agent Skills — each with explicit trigger conditions, a step-by-step process with hard gates, and worked historical case studies cited to primary sources. MIT-licensed, 10K+ installs on ClawHub.
Every founder has read about first-principles thinking. Almost no one — human or AI — actually runs it. The method lives in books and blog posts as prose: inspiring to read, impossible to execute. Ask an LLM to "use first principles" and you get vibes — a paragraph that name-checks Musk and then does whatever it was going to do anyway.
We wanted our agents to genuinely run these methods before acting — tear assumptions to bedrock before pricing a product, invert before shipping a launch plan, update like a Bayesian when evidence lands. So we rebuilt 163 mental models as Agent Skills: self-contained SKILL.md files an agent loads and executes. Then we open-sourced all of them under MIT. Here's what "executable" actually took.
A mental model becomes executable when it can fail
The difference between a description and a process is that a process can halt. Each skill has three load-bearing parts most prompt libraries skip:
