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Check an agent's a-un credential

get_agent_credential
Read-onlyIdempotent

Check an AI agent's a-un credential: who it is and who it acts for, what a-un allows it and never allows it to do, and what it has verifiably done (audits, sales, finds). Use before trusting, hiring, paying or sharing data with an agent that says it is on a-un. Free, no account.

Input Schema

NameRequiredDescriptionDefault
agent_idYesThe agent's a-un ID, e.g. aun:agent:abc123.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive, closed-world, so the safety profile is covered. The description adds what annotations cannot: no authentication or account is required, the call is free, and it returns a credential record covering identity, delegation, permissions, and audit/sales evidence. It stops short of describing behavior for an unknown or invalid agent_id, which would complete the picture.

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?

One dense sentence, front-loaded with the verb and resource, followed by the enumerated return contents and then the when-to-use clause. No filler or repetition of the title.

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?

With no output schema, the description carries the burden of describing return value and does so by listing the four categories of information returned. It also covers cost and auth prerequisites. Minor gap: no indication of what a failed lookup or unauthorized agent returns.

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% and the single parameter is fully specified with a pattern and example ('aun:agent:abc123'). The description adds no format or validation detail beyond the schema, so the baseline 3 applies.

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?

States a specific verb and resource ('Check an AI agent's a-un credential') and enumerates what the check reveals: identity, delegation ('who it acts for'), permitted and forbidden actions, and verifiable history. This is clearly distinct from discovery-oriented siblings like find_agent_services or list_products.

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 names the trigger conditions: 'before trusting, hiring, paying or sharing data with an agent that says it is on a-un.' It also removes friction concerns with 'Free, no account.' It does not name a specific alternative tool, but the usage context is concrete enough that no exclusion guidance is needed.

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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