CRAWLHIVE + JEV + GROK BOTS: 9 FEATURES IN 3 DAYS. ONE F*CKING PERSON.
repo: https://github.com/h100envy/crawl-hive
three days ago crawlhive was a scanner with crawlers behind it
today it's a different product
every competitor says trust me. we shipped a page that shows every miss we made instead
9 major features. full breakdown of each with real numbers
jev decides if a signal is worth attention in 0.5 seconds for $0.00002
tokens that pumped scored 66–83%, the ones that dumped 49–55%, scam 3%
29 signals cost $0.0008 total
grok bot sits on duty over a crawler and calls LOOK / WATCH / AVOID
jev handles the confident ones, grok gets called only for the doubtful
chatgpt, claude, meta muse, cursor connect in one click via oauth
grok bot via mcp
the agent wakes up only when there's something new and doesn't burn credits for nothing
track record checks every verdict against the real price for 24 hours
the misses are visible on purpose
launch radar scans fresh launches on solana, bnb chain and robinhood chain every 3 minutes
a full app inside telegram: scan, radar, watchlist, crawlers in one bot
answers contract addresses right in groups
watches for rugs for 7 days
24 hours later it tells you itself whether the verdict came true
bnb chain and every solana launchpad including meteora
AI costs dropped 8–50x
ceiling of ~$1.25 a day no matter the traffic
security audit: several agents went through the whole codebase
every finding checked by hand
more than a dozen holes closed before anyone else found them
now the main part
3 hours after launch track record showed a pattern
tokens under a day old with linked wallets and a fresh dev wallet were passing as CLEAN and then rugging
SUKI with 12 linked wallets and a dev under an hour old passed as OK and rugged
we changed the rule the same day
now those tokens can't score above RISKY
that's the whole point of a public track record. it shows where the scanner is weak before the market does
no competitor does this. for them it's still on the roadmap
full breakdown in the article with screenshots and how each piece works inside
which scanner besides us shows you where it got it wrong?