Documentation
Everything you need to know about using Treebeard — from reading ratings to integrating with the API.
Why Treebeard Exists
Treebeard grew out of an investigation into a harder problem: enabling AI agents to participate in economic systems that require trust. As we explored what it would take for marketplaces, protocols, and platforms to rely on autonomous software, one question kept surfacing — how do you evaluate an AI agent you've never interacted with?
Traditional evaluation frameworks don't work here. There's no FICO score for agents, no balance sheet to audit, no management team to interview. But the people relying on them — marketplace operators, DeFi protocols extending credit, developers choosing dependencies, enterprises deploying autonomous workflows — still need signals: Is this agent economically viable? Is it operationally reliable? Does it behave safely? Has it been audited?
That's the gap Treebeard fills. We built an independent, methodology-driven ratings protocol for AI agents — infrastructure that trust-sensitive applications need to function, now applied to the agent economy. Every Treebeard Rating is a structured answer to the question any operator or integrator is really asking: can I rely on this agent?
The space is evolving quickly. Standards like ERC-8004, ERC-8128, and x402 are emerging. New ratings methodologies are being developed across the industry. Treebeard is built to incorporate this evolution — ratings can be derived organically from on-chain signals, or in collaboration with partner ratings services as the ecosystem matures.
How to Read a Rating
Every Treebeard Rating has four components: a letter grade, a numeric score, a confidence percentage, and a trend indicator. Together, they give you a complete picture of an agent's quality.
| Grade | Score Range | Meaning |
|---|---|---|
| A+, A, A- | 90 – 100 | Exceptional |
| B+, B, B- | 75 – 89.9 | Above Average |
| C+, C | 65 – 74.9 | Average |
| C-, D | 40 – 64.9 | Below Average |
| F | 0 – 39.9 | Failing |
Confidence tells you how much verifiable data supports the rating. High (80–100%) means extensive evidence; Low (<50%) means the score may shift as new data arrives.
Trend shows the direction of movement since the last rating epoch — up (▲), stable (—), or down (▼).
For the full breakdown of every grade, sub-grade, and indicator, see the Rating Scale page.
Using the Directory
The Agent Directory is a searchable, filterable database of every AI agent Treebeard has discovered and evaluated.
Search
Type any agent name, description keyword, or chain to find matches instantly.
Filter by Agent Type
Narrow results to Financial, DevTools, Customer Service, Enterprise, Autonomous, Research, or Creative agents.
Filter by Chain
View agents on Base, Solana, Ethereum, Arbitrum, or other supported chains.
Sort
Order by rating, score, trending momentum, or date indexed to find what matters to you.
Click any agent to view its full profile — including metadata, rating breakdown by signal category, rating history, chain deployments, and external links.
Using Leaderboards
The Leaderboards page shows the highest-rated agents across the ecosystem, updated in real-time.
Overall Top 50
The 50 highest-rated agents across all agent types and chains. The default view.
Agent Type Tabs
Switch between the ten agent type categories to see the top agents within each — Financial, DevTools, Customer Service, Enterprise, Autonomous, Research, Creative, Infrastructure, Safety-Critical, Data.
Trending
Agents with the largest positive rating movement over the past 7 or 30 days. Great for spotting emerging quality.
Newly Listed
Recently discovered agents that have entered the Treebeard pipeline, with their current evaluation status.
Rank movement indicators (▲ ▼) show how each agent's position has changed since the previous epoch.
Understanding the Methodology
Treebeard rates agents using six signal categories, each weighted according to the agent's agent type. Signals are sourced from public, verifiable data and weighted by cost-to-fake.
Dive deeper into each category, weight profiles, and scoring mechanics on the Methodology page. For the full rating pipeline, see Our Process.
The ratings landscape itself is evolving. Treebeard is designed to ingest signals from partner ratings services as they emerge — meaning a Treebeard Rating can reflect both organic on-chain evidence and collaborative intelligence from other credible sources in the ecosystem.
For Developers
The Treebeard API provides programmatic access to everything on the platform — agent profiles, ratings, signal breakdowns, leaderboards, and trending data.
REST API
Base URL: https://treebeard-api.onrender.com/v1
Get started with the full API Reference — including authentication, rate limits, code samples, and response formats.