Jev in Practice: Browser Use and Agent Workflows

Six seats including STRAT, EXEC, and SCOUT use Jev as a yes/no judge; the paper run made a daily profit but still lost to simply holding, with a transparent, reviewable process.

After the amount is locked, Jev selects the service, the registry supplies the payee, and Kimi writes the reply; live on Monad mainnet.

A roundup of repos including jev-trader, where Jev places orders on Kuru, and Alpaca terminals and market-maker backtests use it for structured buy/sell calls.

Rebuild the screen around what bots need: Jev answers whether today is worth trading, whether the coin is real, and when to exit, while Grok Bot does the trading.

A roundup of repos including QuantDinger, where Jev vetoes trades before entry, paired with a charting library and a decision model that can't write a word but can veto.

Six Grok agents plus Jev read the 5m chart, and a trade only fires when all five boxes are checked: liquidity sweep, RSI divergence, volume spike, VWAP reclaim and break of structure.

A crawler finds targets and Jev acts as judge, while a newly hired QUANTGPT tunes risk as the paper run works from $100 toward $100K.

The author gave his agents $67 overnight, with Scout, Skeptic, Quant and Risk checking each entry before Jev made the final call, resulting in 15 trades and 11 green.

Over 24 hours a four-seat desk had Jev block toxic order flow, and the author says the account went from $279 to $2,559 under the rule that nothing trades if order flow looks unhealthy.

OpenClaw creator Peter Steinberger published his agent rules and 69 skills under MIT, with one shared AGENTS.MD that Claude Code and Codex read through symlinks.

Monad engineer Jarrod built a trading bot where Jev decides buy or sell from an asset pair's price feed and executes real trades on Kuru's on-chain order book every 300ms block.