Most people see
@sleuthintel and think “Another Crypto Analytics Dashboard.”
I think that misses the point. A simple Read here ⇣ ⇣ ⇣ ⇣
Starting from here ➜ ➜ Crypto already solved execution. Wallets can trade, APIs can move data, and agents can click the button.
▼ The harder problem now is context.
An agent can find a wallet that bought ETH. But can it tell whether that wallet belongs to one trader, a fund spread across five addresses, or someone who just got lucky once?
That’s the problem Sleuth is trying to solve.
Instead of giving agents more alerts, it gives them a context layer around the data.
The interesting part is how they build it.
The Belt is the messy intake layer where claims and intelligence get submitted and checked.
The Tree of Knowledge is what survives that process. Wallets, traders, markets and narratives become connected nodes, with relationships between them.
So instead of:
“Wallet 0x123 bought ETH.”
You get something closer to:
“This wallet has a track record, is connected to these addresses, has been accumulating, while prediction markets are pricing the same direction and CT hasn’t caught up yet.”
That distinction matters because agents don’t naturally question bad data. If you feed an agent “this is smart money,” it can treat that claim as fact.
Sleuth’s reputation system tries to put friction around that.
$SLEUTH is the economic layer. aSLEUTH is earned reputation. You can’t simply buy reputation, and bad intelligence can cost you.
The real test is whether the Belt and Tree can turn a messy stream of crypto information into context agents can actually trust.
If they pull that off, Sleuth becomes more than a dashboard.
It becomes the layer an agent checks before deciding what the data actually means.
NFA. Read the docs, use the terminal, and do your own research.
And mostly importantly get your informations from Sleuth official page
@sleuthintel