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crypto-bd-agent

Production-tested patterns for building AI agents that autonomously discover, > evaluate, and acquire token listings for cryptocurrency exchanges.

Documentation

Crypto BD Agent — Autonomous Business Development for Exchanges

Production-tested patterns for building AI agents that autonomously discover, evaluate, and acquire token listings for cryptocurrency exchanges.

Overview

This skill teaches AI agents systematic crypto business development: discover promising tokens across chains, score them with a 100-point weighted system, verify safety through wallet forensics, and manage outreach pipelines with human-in-the-loop oversight.

Built from production experience running Buzz BD Agent by SolCex Exchange — an autonomous agent on decentralized infrastructure with 13 intelligence sources, x402 micropayments, and dual-chain ERC-8004 registration.

Reference implementation: https://github.com/buzzbysolcex/buzz-bd-agent

When to Use This Skill

  • Building an AI agent for crypto/DeFi business development
  • Creating token evaluation and scoring systems
  • Implementing multi-chain scanning pipelines
  • Setting up autonomous payment workflows (x402)
  • Designing wallet forensics for deployer analysis
  • Managing BD pipelines with human-in-the-loop
  • Registering agents on-chain via ERC-8004
  • Implementing cost-efficient LLM cascades

Do Not Use When

  • Building trading bots (this is BD, not trading)
  • Creating DeFi protocols or smart contracts
  • Non-crypto business development

Architecture

Intelligence Sources (Free + Paid via x402)
        |
        v
  Scoring Engine (100-point weighted)
        |
        v
  Wallet Forensics (deployer verification)
        |
        v
  Pipeline Manager (10-stage tracked)
        |
        v
  Outreach Drafts → Human Approval → Send

LLM Cascade Pattern

Route tasks to the cheapest model that handles them correctly:

Fast/cheap model (routine: tweets, forum posts, pipeline updates)
    ↓ fallback on quality issues
Free API models (scanning, initial scoring, system tasks)
    ↓ fallback
Mid-tier model (outreach drafts, deeper analysis)
    ↓ fallback
Premium model (strategy, wallet forensics, final outreach)

Run a quality gate (10+ test cases) before promoting any new model.


1. Intelligence Gathering

Free-First Principle

Always exhaust free data before paying. Target: $0/day for 90% of intelligence.

Recommended Source Categories

CategoryWhat to TrackExample Sources
DEX DataPrices, liquidity, pairs, chain coverageDexScreener, GeckoTerminal
AI MomentumTrending tokens, catalystsAIXBT or similar trackers
Smart MoneyVC follows, KOL accumulationleak.me, Nansen free, Arkham
Contract SafetyRug scores, LP lock, authoritiesRugCheck
Wallet ForensicsDeployer analysis, fund flowHelius (Solana), Allium (multi-chain)
Web ScrapingProject verification, team infoFirecrawl or similar
On-Chain IdentityAgent registration, trust signalsATV Web3 Identity, ERC-8004
CommunityForum signals, ecosystem intelProtocol forums

Paid Sources (via x402 micropayments)

  • Whale alert services (~$0.10/call, 1-2x daily)
  • Breaking news aggregators (~$0.10/call, 2x daily)
  • Budget: ~$0.30/day = ~$9/month

Rules

  1. Cross-reference: every prospect needs 2+ independent source confirmations
  2. Multi-source cross-match gets +5 score bonus
  3. Track ROI per paid source — did this call produce a qualified prospect?
  4. Store insights in experience memory for continuous calibration

2. Token Scoring (100 Points)

Base Criteria

FactorWeightScoring
Liquidity25%>$500K excellent, $200-500K good, $100K minimum
Market Cap20%>$10M excellent, $1-10M good, $500K-1M acceptable
24h Volume20%>$1M excellent, $500K-1M good, $100-500K acceptable
Social Metrics15%Multi-platform active, 2+ platforms, 1 platform
Token Age10%Established >6mo, moderate 1-6mo, new <1mo
Team Transparency10%Doxxed + active, partial, anonymous

Catalyst Adjustments

Positive: Hackathon win +10, mainnet launch +10, major partnership +10, CEX listing +8, audit +8, multi-source match +5, whale signal +5, wallet verified +3-5, cross-chain deployer +3, net positive wallet +2.

Negative: Rugpull association -15, exploit history -15, mixer funded AUTO REJECT, contract vulnerability -10, serial creator -5, already on major CEXs -5, team controversy -10, deployer dump >50% in 7 days -10 to -15.

Score Actions

RangeAction
85-100 HOTImmediate outreach + wallet forensics
70-84 QualifiedPriority queue + wallet forensics
50-69 WatchMonitor 48 hours
0-49 SkipLog only, no action

3. Wallet Forensics

Run on every token scoring 70+. This differentiates serious BD agents from simple scanners.

5-Step Deployer Analysis

  1. Funded-By — Where did deployer get funds? (exchange, mixer, other wallet)
  2. Balances — Current holdings across chains

Use Cases

  • Building an AI agent for crypto/DeFi business development
  • Creating token evaluation and scoring systems
  • Implementing multi-chain scanning pipelines
  • Setting up autonomous payment workflows (x402)
  • Designing wallet forensics for deployer analysis