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

With no annotations provided, the description carries the full burden of behavioral disclosure. It covers the output format (ACCEPT/REJECT/REVIEW with reason codes, booleans, hashes, evidence packet), the specific checks performed (schema, required fields, freshness, source presence, receipt binding), the limitation (not a quality review), and the payment requirement with an error behavior for missing payment headers. This is exceptionally transparent.

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 dense but well-structured. It front-loads the core purpose and return behavior, then adds checks, use case, and payment details in a logical order. While it is longer than minimal, every sentence contributes necessary information—no redundancy. It earns a 4 rather than 5 because it packs several clauses into single sentences, slightly reducing readability, but overall it is efficient.

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 moderate complexity (2 parameters, no structured output schema, no annotations), the description is quite complete: it explains what it does, what it returns, the checks it performs, and the payment mechanism. It could be improved by specifying the required fields of the query JSON explicitly, but the schema example covers that. The absence of an output schema is compensated by a clear description of the return structure. Overall, it is close to 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?

Schema coverage is 100% for both parameters: query and context have descriptive entries in the schema. The description adds no new parameter-specific meaning beyond what the schema already provides—it mirrors the schema's explanation of the JSON structure. The example in the schema is as informative as the description. Thus, a baseline score of 3 is appropriate; the description doesn't enhance parameter understanding 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 opens with a precise verb and resource: 'Verify a paid deliverable against its offer, original request, payment receipt, and acceptance rules.' It clearly identifies the tool's function and distinguishes it from all sibling tools, which focus on analysis, generation, or research rather than verification. The return values are also explicitly listed, making the purpose unambiguous.

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 explicitly states when to use the tool: 'Use in agent-to-agent purchases before releasing or accepting work.' It also provides a clear exclusion: 'Not a quality review of prose.' Even though no specific alternative tool is named, the context is sufficient because no sibling performs a similar function. This leaves no ambiguity about the appropriate use case.

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