THE CABAL

Education|| Alpha || Gaming || Community.

[pǝuıɐɹp @drained99]

Building for an industry worth trillions of dollars. The goal with DegenLens is simple: provide verifiable on-chain intelligence for the gambling economy, with the help of @Telegraphprotoc.

Today, gambling intelligence is fragmented across blockchain data, casino feeds, provider data, public information, and centralized analytics platforms. It can be difficult to know what is actually happening, where the numbers come from, and whether the conclusions can be trusted.

DegenLens brings these sources together to analyze casinos, game providers, games, players, wallets, transactions, market activity, and suspicious behavior.

You can investigate a casino’s deposits and withdrawals, trace the wallets behind its activity, compare operators and providers, analyze individual player activity and profit/loss over time, and surface unusual patterns across the ecosystem.

But the goal isn't simply to show more data. It's to make the intelligence verifiable.

DegenLens distinguishes between what is directly observed on-chain, what is calculated from observed data, and what is inferred. Each insight should have a clear source, methodology, confidence level, and evidence behind it.

With Telegraph, this intelligence can become a reusable supply layer for applications and AI agents, anf not just another dashboard.

Raw data ➛ intelligence ➛ verification ➛ open access.

[THE CABAL @diicabal]

@thecisco_ @educkcoin D2AB

[THE CABAL @diicabal]

@robidrop 0xb2b0c35500db766675335a10c2ea7adfb63c0b67

[THE CABAL @diicabal]

@Smaris 0x9800ec8b211cf0b85d3936a3694695937ae86db3

[THE CABAL @diicabal]

@thecisco_ @0xNTRPY @deepxhl @JustJay4k @remainskept @SaviCrypto ✨

[PAPITO @papito_dele]

update: krites (#4809) is now live on okx(.)ai

before you hire any agent on the marketplace, run it through krites first.

it live-probes the candidate, checks reachability, payment-protocol compliance, price fairness and whether it actually requires the inputs it claims.

you get back a hire, negotiate, or avoid verdict with reasons.

then stack it with @attestra_ai, krites vets the agent before you pay, attestra sanitizes the response before your llm reads it.

agent #4809. 0.01 usdt per vet. real x402 micropayments on @xlayerofficial

trust is infrastructure. demo dropping soon #okxai

[Attestra @Attestra_ai]

Attestra's trust registry, live so far:

➙ 14 services currently tracked
➙ 14,740 endpoint probes
➙ 12 threats blocked
➙ all service currently tracked can be trusted
➙ 14,762 total attestation calls

We are working on improving Attestra everyday.

Currently hardening each core service. First up: Payload Scan, moving beyond pattern matching to catch injection attacks that don't look like attacks. More soon.

[Attestra @Attestra_ai]

➙ How does an agent know a service works before it pays?
➙ How does it know the ASP will do what it claims?
➙ Who checks the response is safe before the model acts on it?
➙ Who confirms the payment actually settled onchain?

That’s what Attestra is for — trust checks before money moves.

Lookup ➙ Scan ➙ Verify.

https://t.co/WIqddf7Mqa #4726 · X Layer

happy new month everyone.
https://t.co/Yo7LJivMyX

[Attestra @Attestra_ai]

x402 lets agents transact autonomously.

But autonomy creates a trust problem:
➙ How does an agent know a service works before it pays?
➙ How does it know the ASP will do what it claims?
➙ Who checks the response is safe before the model acts on it?
➙ Who confirms the payment actually settled onchain?

That’s what Attestra is for. Trust before money moves.

Lookup ➙ Scan ➙ Verify.

Built on @XLayerOfficial

https://t.co/WIqddf7Mqa #4726 · X Layer

[pǝuıɐɹp @drained99]

I just published Touch-Grass on @glazeapp. Check it out 👇
https://t.co/LRQigBKZWS

The simple Idea: Less scrolling. More living.

Touch Grass is an AI-powered macOS companion that helps you spend more time experiencing the real world and less time wondering what to do.

Instead of endless event lists or generic recommendations, Touch Grass gets to know you, your interests, personality, schedule, budget, and goals, and suggests meaningful activities that fit your lifestyle.

Whether that’s discovering a cozy café, exploring a hidden park, attending a local meetup, visiting a museum, taking a sunset walk, or simply catching up with a friend, every recommendation is tailored specifically to you.

The goal isn’t just to help you “go outside.” It’s to help you build a happier, healthier, and more social life through small, consistent adventures.

Do try it out and give some feedback and recommendations. Thank you.

[Attestra @Attestra_ai]

Agents are expected to be fast. Find a service, pay, get a result in seconds, not hours.

What actually happens when and if an endpoint is dead. Or it works but gives you something totally different from what the listing promised. Or you paid and... that's it. Nothing useful back.

We've been hitting this over and over while building Attestra. It's expensive and it's annoying. So we built a registry that tracks what actually works, not what the listing claims.

Our probes hit endpoints the same way a real buyer/seller agent would: call it, check the response, scan the payload, see if it matches what was advertised.

Works => we log it. Breaks => we log that too. Over time you get a real picture, not one lucky try.

Before your agent pays or trusts the data, we try to answer the obvious stuff:

Can you even reach it?
Is the response safe to feed your model?
Has this service been reliable lately?
Did the onchain payment actually go through?

Probe, scan, attest, verify. that's the loop.

Buyer agents (and facilitators) can hit our API or MCP and check before they spend => who's been passing probes, whose payloads look clean, whose settlements actually verified.

Less guessing. Less USDT thrown at dead ends.

The registry is up. Probes are running. Scores update as we collect more evidence.

We're waiting on @OKX to accept our ASP listing before we ship the next chunk. fuller catalog sync, more paid tools listed, tighter settlement checks on every verdict.

@XLayerOfficial

[Attestra @Attestra_ai]

Attestra is live on OKX.

Before your agent pays another agent, Attestra answers three questions:
1. Can I even reach this service, and does it actually work?
2. Can I trust it to do what it claims, not just what its listing says?
3. Is the response safe for my agent to act on?
4. Has this service been reliable over time, or was it just lucky once?
5. Did the payment actually settle onchain?

That’s it. a trust layer for agent commerce.

➙ Trust Lookup
➙ Payload Scan
➙ Transaction Verify

This is **v1**. OKX + X Layer is the first step.
We’ll keep shipping improvements, and feedback is welcome.

Agent #4726 on https://t.co/WIqddf7Mqa

[Attestra @Attestra_ai]

Building for the X Layer hackathon

The Problem
As autonomous agents begin hiring and paying other agents, trust and security become the primary risk. Agent-to-agent commerce moves at machine speed, but buyer agents still lack reliable answers to the questions that matter before value moves:

➙ Is this ASP actually trustworthy, or just well-listed?
➙ Does its endpoint work, and does the response match what it advertises?
➙ Is the reply safe for an agent to act on, or does it hide injection / wallet-drain intent?
➙ After payment, did settlement really land onchain?

Without those checks, a buyer agent can pay a broken service, act on a malicious payload, or treat a failed transfer as complete, with no human in the loop and no undo.

The Solution
Attestra: a trust layer for agent-to-agent commerce. Live on https://t.co/WIqddf7Mqa as ASP #4726, with x402 settlement on X Layer.

How it solves it
Attestra closes each of those gaps in the buyer-agent loop, before payment, after the ASP responds, and after settlement:
1. Trust Lookup (before pay): The buyer agent looks up the ASP’s live attestation: trust score, verdict (`trusted` / `caution` / `untrusted` / `unproven`), and recent probe history.

Behind the score is a real Endpoint Probe, latency, listing/contract match, and whether the response matches what the service advertises. Freshness decay means stale evidence doesn’t look like trust.
If the verdict fails the threshold, the agent aborts before money moves.

2. Payload Scan (after the ASP responds):
Before the buyer agent’s LLM or wallet acts on the reply, Attestra scans the raw payload for prompt injection, wallet-drain language, phishing, and hidden text.

It returns flags, severity, and a redacted payload. High or critical, use the redacted result or stop. A “trusted” ASP can still return an unsafe response; this step catches that.

3. Transaction Verify (after payment): After x402 settlement on X Layer, the agent verifies the onchain receipt: success status, payee, amount, and USDT transfer logs. If settlement didn’t land as expected, the job is not marked complete.

Build story
Attestra started from one design question: what should a buyer agent verify before value moves and what security gap exist between agent calls? That became an evidence stack. Live Endpoint Probes feeding an attestation registry, Payload Scan before the model acts, and Transaction Verify after x402 settlement on X Layer. so trust is measured from observed behavior, not listing reputation alone.

End-to-end: check trust ➙ call only if clear ➙ sanitize before acting ➙ verify settlement.

🔗 https://t.co/ioKLXH1NPB

[Olivia @Olyvia_Tweets]

an agent marketplace listing is not a contract.

you can pay for an API that's down, returns the wrong shape, or ships a payload your model shouldn't read and autonomous agents won't pause to double check.

@Attestra_ai is the pre-payment trust gate:
→ probe — is the endpoint alive, fast, and returning what was advertised?

→ scan — is the response safe before your LLM reads it?

→ score — availability, integrity, and reputation in one verdict

check first. pay only if trusted.

attestra — the trust layer for agents.

i just submitted our ASP listing to @okx @XLayerOfficial waiting to hear back!

[Olivia @Olyvia_Tweets]

everyone wants autonomous agents

but!!! as the agent market keeps growing, agents will be making more decisions and transacting with one another

which makes trust and security very important

that’s where @Attestra_ai comes in

with Attestra_ai, agents check :
- if an endpoint actually works before calling it
- scan a payload for prompt injection or hidden instructions before reading it
- know a service's reputation score before paying it

i’ll be dropping more info soon, be there!!

@Attestra_ai @XLayerOfficial

[THE CABAL @diicabal]

@thecisco_ @Racerz_eth @Michelangel_art gVroom racer!

[THE CABAL @diicabal]

@thecisco_ @Gloombles @byVmeta @mylesdaughtry this is alpha, @byVmeta ✨

[THE CABAL @diicabal]

@cfc_duran gud call

[THE CABAL @diicabal]

@thecisco_ @Gloombles @byVmeta ✨

[THE CABAL @diicabal]

@thecisco_ @adamilenich looks good!