Verify Agent Recognition Proof

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

Annotations provide readOnlyHint=true, which matches the verification nature. The description adds 'replay-safe' and context derivation, but overall behavioral detail beyond annotations is minimal. No contradictions with annotations.

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

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

Two brief sentences that front-load the core action and key constraints. Every word contributes information with no redundancy.

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

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

Despite having an output schema and complex parameters, the description is sparse. It does not explain return values, proof structure, or edge cases, leaving gaps for an AI agent to correctly invoke the tool.

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

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

Schema description coverage is 0%, so the description must compensate. It mentions 'expected purpose and request envelope' linking to two parameters, but provides no details on the 'proof' parameter, which is a complex object. The description adds limited meaning beyond the schema.

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

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

The description clearly states the verb 'Verify' and the resource 'AgentRecognitionProofV1', specifying the action and the object. It distinguishes the tool from siblings by naming a specific proof type and including 'expected purpose and request envelope', which is unique among the sibling tools.

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

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

The description implies usage context (authenticated MCP session) but does not explicitly state when to use or avoid this tool. No alternatives or exclusions are mentioned, leaving the agent to infer usage from the sibling tool names.

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