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Verify Agent Trust

verify_agent_trust
Read-onlyIdempotent

Verify an AI agent's identity (KYA-OS DID) and behavioral trust score. Returns a signed Ed25519 TrustVerification envelope with fail-closed attestation. Compliance: EU AI Act Art. 14, KYA-OS. Cost $0.01 per call.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contextNoOptional verification context (default 'mrv_verification').
agent_didYesAgent DID to verify (KYA-OS URN, e.g., 'urn:aid:innovalyxx:sovereign-edge').

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okNoTrue when the tool completed without a validation error.
tierNoTrust tier label.
toolNoTool name that produced this payload.
paymentNoSettlement receipt after x402 or sandbox payment.
verifiedNoWhether the agent passed the trust threshold.
agent_didNoCanonical DID that was scored.
trust_scoreNoHeuristic trust score in [0, 1].

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds valuable behavioral context: returns a signed Ed25519 envelope, fail-closed attestation, compliance references, and cost per call. This goes beyond what annotations provide.

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?

Three sentences with zero waste. The core purpose is front-loaded, followed by the return type, behavioral guarantee, compliance context, and cost. Every sentence earns its place.

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

Completeness4/5

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

The tool has an output schema, so return values are documented elsewhere. The description covers purpose, return type, behavioral guarantee, compliance, and cost. It could mention what 'fail-closed' means in practice or when verification would fail, but for a read-only verification tool with an output schema, this is largely complete.

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?

Schema description coverage is 100%, so the schema already documents both parameters (agent_did and context). The description adds the default context value ('mrv_verification') and an example DID format, which is helpful but not extensive. Baseline 3 is appropriate since the schema carries the parameter documentation burden.

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 clearly states the tool verifies an AI agent's identity (KYA-OS DID) and behavioral trust score, and returns a signed Ed25519 TrustVerification envelope. It distinguishes itself from siblings like verify_agent_attestation and verify_agent_reputation by focusing on identity + trust score with a fail-closed attestation.

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?

The description implies when to use this tool (verifying an agent's identity and trust score) and mentions compliance context (EU AI Act Art. 14, KYA-OS). It doesn't explicitly name alternatives or exclusions, but the sibling list and the specific KYA-OS DID focus provide enough context for an agent to select it over verify_agent_attestation or verify_agent_reputation.

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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