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

With no annotations, the description carries the full disclosure burden. It does well by explicitly stating that standards with proprietary control lists are named without reference numbers, and that this is intentional. This is a meaningful behavioral caveat beyond the basic list semantics, though it does not describe every possible edge behavior.

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 tight sentences with no filler. The first sentence front-loads the main deliverables, and the second adds an important caveat about proprietary control lists. Every sentence earns its place.

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 zero-parameter, no-output-schema tool, the description is complete: it states what is listed, what counts are included, what related data is cited, and the one intentional omission. An agent has enough information to select and invoke this tool correctly.

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 is an empty object with 100% coverage, so there are no parameter semantics to clarify. The description adds useful context about the returned information, which is more than needed for a parameterless tool.

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 names a specific verb and resource: it lists the questionnaire standards a corpus covers, including question counts and cited controls. This content is clearly distinct from sibling tools like get_question or search_questions, which focus on individual questions or statistics rather than standards coverage.

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 intended use is implied: an agent should call this when it needs an overview of which standards the corpus addresses and how questions/controls map to them. However, there is no explicit when-to-use guidance, no exclusions, and no references to alternatives such as get_questionnaire_statistics for other summary needs.

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