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

There are no annotations provided, so the description carries the full burden. It discloses that each check is 'probed against the primary source, not the claimant,' and explains the output statuses (PASS/FAIL/UNVERIFIABLE) and their semantics, including the crucial note that UNVERIFIABLE is never reported as PASS. However, it does not mention whether the tool has side effects (e.g., network calls, costs), authentication requirements, or any mutating behavior. Given its role as a verifier, it is likely read-only, but this is not explicitly stated.

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 lengthy but information-dense, covering purpose, request format, check types, output semantics, and usage examples. It front-loads the purpose and request format, and uses a concise listing of check types. While some redundancy exists (e.g., explaining UNVERIFIABLE twice), the structure is logical and each sentence contributes value to the tool's comprehension.

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?

Given the tool's complexity (multiple check types, output semantics), the description is quite thorough. It explains the output structure (per-check status, raw evidence, reproduce command, overall verdict) and clarifies ambiguous cases. The main gap is the empty input schema, which forces reliance on the description for request construction, but the description handles this reasonably. It also lacks error-handling details for malformed checks, but that is a minor omission for a verification 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?

The input schema is empty (0 parameters), so the description is the sole source of parameter meaning. It compensates by specifying the POST body format: '{"claim":"...","checks":[...]}' and listing the supported check types (http, evm_balance, evm_call, evm_tx, dns, x402, x402_enforce, hash) with brief explanations of each. It does not provide a full JSON schema for the checks array, but the enumeration is detailed enough for an agent to construct valid requests.

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 tool's purpose: 'Verify or refute a machine-checkable claim before you pay anyone.' It specifies the action (verify/refute), the resource (machine-checkable claims), and gives concrete examples of use ('another agent's stated numbers, treasury balance, payment address...'). It distinguishes itself from the many x402 sibling tools by focusing on adversarial claim verification rather than generic data lookups.

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?

It provides explicit usage context: 'Use it on another agent's stated numbers, treasury balance, payment address, contract ownership or x402 pricing.' It also explains the request format (POST with claim and checks). However, it does not explicitly mention when not to use this tool or name alternative tools, though the sibling list is vast and none directly overlap with this adversarial verification role.

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