AdvaithD

Pumpfun Scope Data Source Map

This maps each Scope-facing data point to where it comes from, how we index it, where we aggregate it, and how it reaches the Scope page.

High-Level Rule

Scope should not infer Pumpfun protocol state in the browser.

The data should flow like this:

AdvaithD

Pumpfun Scope Data Plan: Metadata, Events, Rollups, Talos, Scope

Goal

Surface Pumpfun-specific token/program data on Scope cards, hovers, filters, chart markers, and tradefeed labels.

This includes offchain-created coins, Mayhem mode, creator rewards, creator fee claims/payouts, charity coins, agent coins, agent revenue, buybacks, claimed/unclaimed, payment authority, and Mayhem bot trade tagging.

The core design is two data paths:

AdvaithD

Pumpfun Data on Scope: Executive Summary

What We Are Building

We want Scope cards to show richer Pumpfun context directly on the token card:

• Agent coin status
• Mayhem mode status and countdown
• Creator rewards / fee sharing
• Charity coin details

AdvaithD

Staging Web Performance Deep Dive (2026-04-15, Expanded Dataset)

Scope

• Target app: azura-monorepo/apps/web
• Focus routes: /scope, /markets/spot*, /markets/pair-scanner, and broad /spot/:chainId/:token coverage
• Trace scope: web -> tRPC -> API -> Talos-v2 and adjacent backends
• Included data: 16 labeled staging runs + 40-sample scope click probe

Dataset Summary

AdvaithD

Prod-v2 Memetics Agentic Empty Tab Runbook

Date: 2026-04-08

Summary

The memetics "agentic" tab is empty in prod-v2 because prod Talos state-service is missing v4 pool mappings for agentic pools that do exist in ClickHouse. Nonprod works because it materializes those v4 pools into Talos state correctly.

This is not a frontend bug.

AdvaithD

0 · About the User and Your Role

• The person you are assisting is User.
• Assume User is an experienced senior backend/database engineer, familiar with mainstream languages and their ecosystems such as Rust, Go, and Python.
• User values "Slow is Fast", focusing on: reasoning quality, abstraction and architecture, long-term maintainability, rather than short-term speed.
• Your core objectives:
  • As a strong reasoning, strong planning coding assistant, provide high-quality solutions and implementations in as few interactions as possible;
  • Prioritize getting it right the first time, avoiding superficial answers and unnecessary clarifications.

---

AdvaithD

package main

import (
    "bufio"
    "fmt"
    "log"
    "os"
    "strings"

    "github.com/ethereum/go-ethereum/accounts/abi"

AdvaithD

36 - CALLDATASIZE
3d - RETURNDATASIZE
3d - RETURNDATASIZE
37 - CALLDATACOPY
3d - RETURNDATASIZE
3d - RETURNDATASIZE
3d - RETURNDATASIZE
36 - CALLDATASIZE
3d - RETURNDATASIZE

AdvaithD

func register_voter{
        syscall_ptr : felt*, range_check_ptr, pedersen_ptr : HashBuiltin*,
        ecdsa_ptr : SignatureBuiltin*}(poll_id : felt, voter_public_key : felt, r : felt, s : felt):
    let (owner_pubkey) = poll_owner_public_key.read(poll_id=poll_id)
    # verify valid poll
    assert_not_zero(owner_pubkey)

    # verify signature
    let (message) = hash2{hash_ptr=pedersen_ptr}(x=poll_id, y=voter_public_key)
    verify_ecdsa_signature(message=message, public_key=owner_pubkey, signature_r=r, signature_s=s)

AdvaithD

func StreamNewTxs(rpcClient *rpc.Client, fullMode bool) {

	// Go channel to pipe data from client subscription
	newTxsChannel := make(chan common.Hash)

	// Subscribe to receive one time events for new txs
	rpcClient.EthSubscribe(
		context.Background(), newTxsChannel, "newPendingTransactions", // no additional args
	)
	client := GetCurrentClient()