Crypto Bd Agent

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

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

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

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