| name | crypto-bd-agent |
| description | Production-tested patterns for building AI agents that autonomously discover, > evaluate, and acquire token listings for cryptocurrency exchanges. |
| type | skill |
| created | 2026-02-27T00:00:00.000Z |
| domain | life-learning |
| category | finance |
| risk | safe |
| source | community |
| tags | ["skill","life-learning","finance","crypto","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)
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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.
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