README
AI argues. Code settles. The losses stay on the page.
Live dashboard · Daily briefs · 简体中文
| 169 | 1149 | 192 | 48 | 5 | 0 |
|---|---|---|---|---|---|
| days live on a real HK + US account | decisions on the public ledger | episodes settled by code | data modules across 8 layers | agent harnesses, one contract | scores the model wrote for itself |
Numbers and charts refresh weekly; the live dashboard updates through the trading day.
What you get
clawock helps your AI agent analyze your Hong Kong or US holdings and write a trading plan: buy, sell or wait, the case on both sides, and the prices that would change the call. You place the orders. Code later checks each call against market prices and saves the result for the agent to read next time.
That loop is what RSI, Recursive Self-Improvement, means here. Saved evidence and results give the agent something to review before its next decision. The author's daily jobs add connected data feeds, a scheduler and accumulated history; a new installation brings its own, or starts from the single-run example.
[!IMPORTANT] This is not a promise of returns. The calls that told the author to act have not been shown to beat a coin flip.
One real call runs through this page: Goldwind (02208, Hong Kong) on the morning of 2026-10-08. The plan said keep holding and watch, add only above 8.97. The ledger records loss because the price fell by the next session's close; that scores the holding judgment, not a purchase at 8.97.
The plan's indicators came from plugins. A strategy may search for better settings of its own, but adopting them requires a person's review. Try it in five minutes.
Everything that computes is a plugin; what a result may do is not
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