Built to turn over value.

The bottleneck was never ideas. It was reading.

I built RockTurners because I kept losing the same race against my own reading list.

I'd run a screen and come out with a hundred names that fit. That's where the screener quit and the work began. Every one of those hundred was a 10-K to read, footnotes to reconcile, numbers to check against the narrative. Done honestly, I managed maybe a dozen a year. The other eighty-plus stayed a pile — and the company I was hunting for might have been in it.

Capable AI models changed the math. Not by skipping the reading, but by doing far more of it, the same way every time. It started as a single page I wrote for myself. It became RockTurners.

This is a tool for people who want to know the business behind the ticker. If you hold for years, the filings are the research. If you trade momentum, or trade within the day, they show what the company you're trading does, how it makes money and what its filings flag as risks. RockTurners doesn't time entries or exits. Its screens and verdicts run on end-of-day prices; only a price alert you set checks an intraday price. It reads filings and applies published frameworks, whatever the holding period.

The frameworks that matter in investing are published. Graham wrote his down. So did Lynch, and Fisher, and the academics behind the momentum literature. What none of them could give you is the time to apply their discipline to thousands of companies — reading the filings, checking the numbers against the words, hunting for the reasons a thesis fails.

RockTurners exists to do that reading — the same way for every company, impersonally, naming the filing sections it cites. It doesn't have opinions about what you should do. It has evidence about what the filings say, organized by disciplines that have been public for decades.

The gaps stay visible, the citations name the filing and section, and the verdict vocabulary stays honest: a Gemstone is a strong match to a framework — nothing more, and nothing less.