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

With no annotations provided, the description bears full responsibility for behavioral disclosure. It reveals the read-only nature ('look up'), the data source (signed on-chain proofs, ensuring verifiability), and the cost ($0.01 USDC per call), which is valuable operational context. It does not mention failure modes, latency, or rate limits, but for a simple lookup tool these are minor omissions. No contradiction with annotations exists.

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?

The description is two sentences, with the core purpose front-loaded and additional context (data source and cost) appended succinctly. There is no redundancy or filler. Every clause adds value, making it an exemplary model of concise, structured documentation.

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?

The description covers the primary purpose, data source, and cost, and hints at the return content (jobs, disputes, trust-score trend). However, it omits crucial parameter guidance (the 'task' ambiguity) and any prerequisites or limitations (e.g., which chains or proof formats are supported). No output schema exists, so the description could better specify what the agent will receive. These gaps make it adequate but not fully complete.

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?

The sole parameter 'task' is described in the schema as 'Task/query text for this SKU,' which is vague and does not align with the tool's purpose of looking up an agent's track record. The tool description does not clarify what should be passed (e.g., agent address, name, or ID). Even though schema coverage is 100%, the semantic meaning is ambiguous, and the description fails to compensate for this gap. The agent would struggle to know what value to supply.

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 action ('look up') and resource ('an agent's settlement track record'), and enumerates the content (completed vs. failed jobs, dispute history, trust-score trend) plus the data source (signed on-chain proofs). It explicitly distinguishes from self-reported claims, which separates it from generic reputation tools. The verb and resource are specific, and the description differentiates from sibling trust tools by emphasizing on-chain verification.

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 gives an explicit usage context: 'before you transact with it,' which tells the agent when to invoke it. It also contrasts with self-reported claims, implying a reliability advantage. However, it does not explicitly name alternative tools or state when not to use it, despite several sibling tools (e.g., agent.trust-badge, procurement.vendor-vetting) serving similar trust-assessment purposes. A clear alternative reference would earn a 5.

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