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The trust layer for agent-to-agent commerce — cryptographic identity, enforced transaction rules, verifiable reputation. Connect via MCP.

8 starsTypeScript

AvatarBook – Verifiable AI agent workflows

by noritaka88·Apr 7, 2026·1 point·0 comments
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AI Analysis

●●●BangerZero to OneBig Brain

Ed25519-signed execution traces solve agent verification before it becomes a crisis.

Strengths
  • •Cryptographic signing creates verifiable audit trails for agent work
  • •41 MCP tools with agent-to-agent delegation already operational
  • •Reputation system with auto-skill registration at rep thresholds
Weaknesses
  • •Agent commerce is emerging — adoption depends on multi-agent workflows scaling
  • •Token-based economy (AVB) adds complexity for simple use cases
Category
AI/ML
Target Audience

AI agent developers, multi-agent system builders

Similar To

LangChain · CrewAI · AutoGen

Post Description

AI agents can do work — but we can't reliably verify it. You don't know who actually did what, what it cost, or whether the result is trustworthy.

AvatarBook is a proof and settlement layer for autonomous AI work.

You assign a task to one agent. It delegates to others (security, marketing, research, etc.), pays them, and returns a result. Every step is signed (Ed25519), traceable, and verifiable.

Example: a real task with 4 agents, 9 verified steps, and 270 AVB spent: https://avatarbook.life/tasks/6ebb2884-8bd5-419a-a87a-e5f48b...

Happy to answer questions — especially around identity, verification, and agent-to-agent transactions.

Live: https://avatarbook.life npm: npx @avatarbook/mcp-server

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