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 states that the tool lists all tools with pricing and input requirements, which is a clear, read-only operation. It doesn't disclose whether auth is needed or if there is any cost, but for a simple list tool this is adequate.

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 a single sentence that is concise, front-loaded, and contains no filler. Every word contributes meaning, covering what the tool does and when to use it.

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?

For a simple, parameterless discovery tool, the description is fully sufficient. It explains the return contents (pricing and input requirements) and the use case, and no output schema is present, so the description does not need to explain return values beyond what it already states.

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 tool has zero parameters and the schema description coverage is 100%. Per the rubric, a baseline of 4 is appropriate when there are no parameters, as the schema already provides complete information.

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 uses a specific verb ('List'), names the resource ('all available Harvey Verify tools'), and specifies the content ('pricing and input requirements'). This clearly distinguishes it from sibling tools like 'get_service_quality' or 'verify_outcome', which are domain operations rather than a discovery/meta tool.

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 phrase 'Use this for discovery' provides clear context for when the tool should be invoked. However, it does not mention when not to use it or name alternatives, so it lacks explicit exclusions or alternative references.

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