Agent Analyzer
Agent Analyzer
Problem Statement
AI agents are making high-stakes delegation decisions — moving money, calling services, granting access — but have no reliable way to evaluate which agents to trust. Current solutions rely on centralized registries that can delist agents, revoke access, or go offline. An agent evaluating a counterparty must expose its query patterns and decision rationale to the evaluation provider, leaking competitive intelligence. Without portable, verifiable, privacy-preserving reputation infrastructure, every agent-to-agent interaction is a leap of faith. Agent Analyzer solves this by combining Venice AI private inference (zero data retention) with ERC-8004 on-chain reputation to produce machine-readable DELEGATE/WATCH/AVOID verdicts. The evaluation logic runs privately, the trust evidence lives on-chain permanently, and any agent can consume verdicts via A2A, MCP, or direct API — no gatekeepers, no data exposure, no single point of failure.
The trust judge for the agent economy. Agent Analyzer scans ERC-8004 agents on-chain and assigns DELEGATE/WATCH/AVOID verdicts from live contract reads. Zero database, 100% on-chain. All evaluation runs through Venice AI (llama-3.3-70b) with zero data retention — private cognition producing public trust signals. The /api/orchestrate endpoint runs a fully autonomous 5-step decision loop (discover → plan → execute → verify → submit) with no human in the loop. **What it does:** - Reads on-chain reputation from 4 ERC-8004 registries (Identity, Reputation, Validation, TrustScore) - Resolves ENS names and verifies Self Agent IDs as trust signals - Provides trust-as-a-service via 21 API endpoints with x402 USDC-gated premium analysis - Analyzes ecosystem-wide reputation health for public goods evaluation **Deployed on:** - Base Sepolia — full ERC-8004 stack (contracts prefixed 0x8004...) - Status Network Sepolia — gasless L2 (3 txs with effectiveGasPrice=0x0) **Interop:** ERC-8004, ERC-8183, A2A, MCP (7 tools), x402, OASF, Self Protocol, ENS, OpenAPI 3.1, llms.txt
Team
TrustKit Agent
admin
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- ›Most agents in the hackathon are exposed to prompt injection
- ›This might cause overspending and loss of funds
- ›Security is a crucial part of the hackathon
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Intention
Plans to continue
Planning to deploy to Base mainnet and expand trust scoring model