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Errr wait so how am I/mods supposed to discover good new potential channel members? They need to dm us or we need to just happen to see their casts in another channel?

headmaster @duneanalytics, previously mirror and consensys

does anyone have insight on how blob data encoding works on arbitrum and base/optimism? do they have any docs that show how they end up with something like this? https://storage.googleapis.com/blobscan-production/1/01/c8/b9/01c8b924fc972e9d23d46e71478cbbc20a2263d3599e89904a1900f80fdc64af.txt

cc @msilb7 @hildobby

Don't remember if I shared: Publicized my logic to ~approximate duplicate/spam activity (input to ~likely sybils)

Why open it up? Encourage more open models, so we can progress & stop people from using "active addresses"

Still messy, but you can see ideas: https://dune.com/queries/3783798

NOTE: Not for production

data @ op labs, building @optimism 🔴✨ | go /gators 🐊  | casts are my own things | msilb7.com

Was looking into Solayer and liquid restaking on Solana today, and 2 things surprised me 
1/ >90% SOL staked are native stake 
2/ Altho Marinade (mSOL) is still growing a lot in TVL, @jito is absolutely dominating in growth and now takes up 50%+ marketshare in SOL Staked in LSTs

Why is that?🤔

Also curious to see we have similar stats for restaking on Ethereum/EigenLayer already?👀 cc @eekeyguyy @yulia @tomwanhh 

Shoutout to chad @ilemi for the charts🙏

Developer Relations @dune.eth 🧙🤝 | community(openness, crypto) = web3 data | Tinker about human existence ✨🤖⌛🔁

TIL MM swaps is doing more fees than Base.

Can someone help me make a dune, or link me to one that already exists, of the onchain products produced by ConsenSys and Coinbase? eg Linea and/or MM swaps vs Base fees/rev, unique wallets, txn count, etc.

Will tip if this becomes a bigger dashboard that someone creates from scratch.

Placed 100+ in crypto /jobs. Found the gaps, fixing them. 3x grant-backed founder building @interestedfyi to reshape onchain hiring. Ex @ConsenSysMesh.

who’s got the best API for address clustering? 

ie: for a given address return addresses very likely owned by the same person (based on transfer patterns)

What is the typical duration that users keep their bridged funds on Layer 2 solutions before moving them back to the Ethereum mainnet?

https://x.com/optimismgov/status/1828148006950183132?s=46

💫 ZK Rollups are constantly innovating to reducing their L1 gas spend! 

Last week on Aug 21, @scrollzkp's Darwin upgrade went live. It uses single aggregated proofs for multiple batches and eliminates the need to finalize each one individually. 

As you can see here,  we can observe a massive drop in daily ZKP (zero-knowledge proof) verification spend (in ETH) below. 

Note: L1 gas spend for Scroll consists of three parts 1/ proof verification 2/ data availability and 3/ proof hardware. Part 1 for proof verification consumes the most cost.

Scroll isn't alone—ZkSync Era, Linea, and Starknet are all innovating to reduce fees for users via bundling, parallelization and more. The future is more affordable on-chain activity! 💫

- Reference query https://dune.com/queries/4017703/6763457?sidebar=none
- Dashboard on ZKP Verification https://dune.com/nebra/zero-knowledge-proof-verification-cost-ethereum
- Post on Darwin Upgrade https://scroll.io/blog/proof-recursion-scrolls-darwin-upgrade

"Staking Activity on DEGEN"

If I asked you to build dashboards for this, would it be accurate? Or not? I bet a lot of the time, it would be wrong.

Here's why.

If you wrote your query to show staking activity on DEGEN, there is a chance your data is wrong if you started with the assumption that "Deposit function on xyz contract = Stake".

EXAMPLE

If you browse the MasterChef contract on DEGEN, all of the tx functions are simply "Deposit" or "Withdraw".

And, if you analyze the txns correctly, (nearly 100% of the time) the tx classification is either "Stake" or "Unstake".

Deposit = Stake
Withdraw = Unstake

Straightforward, right? Wrong.

The attached example shows a tx with the "Deposit" function, which would normally be classified as "Stake".

But, if you analyze the tx correctly, the classification is "Claim Rewards".

See the problem?

Wrong Classifications = Wrong Dashboards

Is Solana all wash trading? Volume there and specifically on pump.fun are outrageous 

Good for them I guess. Just seems hard to believe

anyone have an example oapps (layerzero)? and know if it is connected to their DVN at all? Trying to track cross chain messages from different providers and can't find any layerzero examples lol.

whats the best dataset for erc20 tokens tagged or labeled by category like "memecoin", "LST", "veToken" kinda thing?

im sure theres many many options but im curious what the community thinks is the highest quality dataset

Some good competition finally! 

https://x.com/clickhousedb/status/1821192971896627585?s=46&t=zBknPbvlo1Ud64d01-RVrg

what % of moxie claimers have purchased a fan token? 

my guess is numba still low cuz mfs only beginning to understand now?

I'm sick of exploring a new L2 or L3 ecosystem and having the same terrible data experience on every explorer, wallet, dApp, etc.

"Just a skill issue"
"Real degens can read it"
"Not a problem for our users"

I mean, sure, whatever.

But, for too long, the entire industry has been pretending like non-technical-users will one day become advanced enough where raw blockchain data isn't an issue.

They're wrong. It's getting worse.

We need to move on from the "Raw Data Standard" and level up to a "Translated Data Standard".

(btw, I know /noves isn't the only one working on this solution, which is great, I'm really stoked about that actually - /onceupon /zapper)

Transaction data is boring, and unsexy, I get it. But it is essential for a better UX for all devs, users, gamers, accountants, etc.

So, I'm asking FOR REAL,

If you're building an L2 or L3 chain, why the hell aren't you already doing this? I genuinely want to understand.

"Does /noves do Cosmos chains?"

Let's see...

Bounty, 5000 DEGEN 💰

REQUIREMENTS:

1. Classify the tx e.g. "Stake"
2. Describe the tx e.g. "Staked 100 TIA"

@bountybot | @bytecast

I’ll make this a bytelight question - give an answer query that has a percentage breakdown of top level casts that have a question mark. What percentage will it be over time? :)

if i hypothetically did some talk/workshop around superchain data, what would be fun to cover?

maxxing on /morpho 🦋 | pursuing a higher self w /higher-athletics | consistently curious

The Bytexplorer bot - tag me to nominate great data questions to earn ByteLight tokens