Tracea

verify_agent

Verify an AI agent's on-chain legal identity on Tracea (Base Sepolia). Returns registration status, financial cap, permission scope, revocation status, and KYA legal identity (mandant) when available. Use this BEFORE trusting or delegating work to an agent.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "agent_address": "<agent_address>"
    },
    "name": "verify_agent"
  }
}

Input Schema

Name	Required	Description	Default
`agent_address`	Yes	Ethereum address of the agent (0x...)

Schema Changelog

Changes observed during successful MCP inspections.

First observedAug 2, 2026

TDQS

A4.1/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It adds value by disclosing the return fields (registration status, financial cap, etc.) and the 'when available' qualifier for the mandant, but it does not disclose potential errors, network dependencies, or side effects (though read-only is implied).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two well-structured sentences. The first states purpose and output; the second provides usage guidance. No waste, fully front-loaded with the core purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple one-parameter tool with no output schema and no annotations, the description covers purpose, return values, and usage context sufficiently. It is complete for an agent to select and invoke appropriately.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema fully describes the single parameter 'agent_address' with its format, achieving 100% coverage. The description does not add additional parameter semantics, so the baseline of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb 'Verify' with a clear resource ('AI agent's on-chain legal identity on Tracea (Base Sepolia)') and enumerates the specific verification attributes returned. This distinguishes it from sibling tools like 'get_agent_info' by emphasizing the legal identity verification purpose and the 'BEFORE trusting' use case.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states when to use: 'Use this BEFORE trusting or delegating work to an agent.' This provides clear context for adoption. However, it does not mention alternatives or when not to use, so it falls short of the full 5 criteria.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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