Blog
Insights, analysis, and updates from the Treebeard team on AI agent ratings and the agent economy.
The Trust Gap
47,816 new ERC-8004 agents in 49 days. Treebeard has rated 99.4% of them. The grade distribution has a structural B− ceiling, and only four agents in the entire 226,000-agent corpus can do cross-chain coordination. This post measures the gap between registry growth and capability — and what it means if you're selecting, building, or building infrastructure for agents.
Read article →Where the Agents Actually Live
Treebeard rates AI agents across 21 chains. The largest single chain is BSC, with 81,492 indexed agents, ahead of Ethereum (64,262) and Base (36,334). We did not plan it that way. We crawled the chains that had ERC-8004 deployments. The post explains what chain-neutrality means structurally.
Read article →Pay.sh and the Provenance Gap
The Solana Foundation and Google Cloud launched Pay.sh with 72 providers. The catalog does not say which are first-party and which are third-party wrappers. The gap is exactly what Treebeard rates. Companion to the labeled catalog at /research/pay-sh-provenance.
Read article →The Treebeard Methodology: A Continuous Trust Layer for the Agent Economy
v4.0 of the Treebeard methodology, published today. Seven signal categories, a non-substitutable safety floor, and two source-level corrections that distinguish a usable trust layer from a credible-looking but silently wrong one.
Read article →The 2008 Question Every Agent Rater Has to Answer
Why opacity in calibration is not the same as opacity in methodology, and why the structural protections matter more than weight publication.
Read article →The 5 Reasons Nobody Trusts Your AI Agent
Of 230,000+ agents indexed by Treebeard, fewer than 1% rate B or above. Here's what separates the top-rated agents from the rest — and what you can do about it.
Read article →Why We Built Treebeard
Over 230,000 AI agents are registered on-chain. As agents become counterparties — acting autonomously, transacting independently — trust requires continuous monitoring. This is the layer we're building.
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