DeFi
YieldRadar: Building a DeFi Yield Intelligence Bot
How I built a multi-factor risk scoring system for 18K+ DeFi yield pools, from scratch to production Telegram bot.
Finding good DeFi yields is easy. Finding safe ones isn’t.
There are 18,000+ liquidity pools across chains. Most yield aggregators show APY and nothing else. But APY without risk context is dangerous — that 200% yield might come from an unaudited contract with a rugpull-able token.
The Problem
I wanted:
- Real-time monitoring of yield pools across multiple chains
- Risk assessment that goes beyond “APY looks good”
- Push notifications when opportunities match my criteria
- All from Telegram, because that’s where I live
No existing tool did this. DeFiLlama has great data but no alerting. Trading bots on Telegram focus on buying/selling, not yield monitoring. Dashboard apps (DeBank, Zapper) require you to open them — no push.
The Architecture
Data pipeline: DeFiLlama API → TypeScript ingestion → Redis caching → Multi-factor scoring engine → Telegram delivery
Risk scoring factors:
- Pool age — new pools are riskier
- TVL stability — volatile TVL = unstable yields
- Token security — mintable, honeypot, proxy contracts (via GoPlus)
- APY sustainability — comparing 24h vs 7d vs 30d APY trends
- Chain risk — L2 vs L1 considerations
Tech stack: TypeScript, Node.js, SQLite (via better-sqlite3), Redis, Telegram Bot API, DeFiLlama API, GoPlus Security API
What I Learned
- Data normalization is the hard part. Every chain reports APY differently. Some include fee APY, some don’t. Some report in real terms, others in nominal. Normalizing 18K+ pools into a consistent format took more work than the entire scoring engine.
- API rate limits are brutal. GoPlus gives you 4K requests/day on free tier. When you’re scoring thousands of pools, you need aggressive caching and smart queue management.
- Telegram is a surprisingly good delivery surface. Inline keyboards, digest formatting, user preferences — it’s a full UX platform.
What’s Next
Pivoting from a Telegram bot to a proper API product. The data pipeline and scoring engine are the real value — wrapping them in a REST/GraphQL API for portfolio trackers and integrators to consume.
More on that soon.