I stopped shipping features on @smartflowradar this week and did something I'd been avoiding: checked how the calls actually performed The good: it catches real moves. A real chunk of calls ran, some hit solid multiples — the signal detection is doing its job finding where money is flowing. The honest gap: I'd been scoring calls by their PEAK price, so a token that pumped then dumped still counted as a "win" — the metric couldn't see a rug. When I measured where calls actually land by day 7: ~24% green, and most fade or nuke. Median call peaks ~1.2x. That's the real challenge, and I'd rather name it than hide it. A few things digging in taught me: • Bigger smart-money buys didn't mean better calls — the heaviest buys rugged more. Often I was catching the top of a coordinated pump, not the start. • The cleanest rug tell was volume-vs-marketcap: tokens churning at ~4x their MC nuked; ones trading near 1x held. Simple filter I wasn't using. • Almost all my calls came from a single trigger — not enough diversification. What's next: • score realized outcome + rug rate, not just peak • filter the high-churn setups • weight smart money smarter • validate every call against live market data at post time • diversify the signals The engine for finding flow is there. The work now is making the calls survive — and measuring it honestly. Building it in the open; I'll post the before/after as the numbers move.

📡 $PAWS — passed every gate, smart money accumulating 🧠 3 tracked wallets in · +$636 net in · holders clean · liquidity healthy ⛓ Solana · MC $60K

📡 $WORTH — passed every gate, smart money accumulating 🧠 3 tracked wallets in · +$2K net in · holders clean · liquidity healthy ⛓ Base · MC $427K @WorthOnBase