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

With no annotations, the description carries the full burden. It doesn't say what the response looks like (prose vs structured tables), how large it is, or that it performs no computation — all of which matter for an agent deciding whether to call it or `calculate`.

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?

It is a single clause with no waste, but it is a noun-phrase fragment rather than a sentence, and it front-loads content enumeration instead of the action the tool performs.

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-annotation, no-output-schema tool, the listing of covered content (inputs, outputs, assumptions, tables) is reasonably complete. What's missing is the relationship to `calculate` and the shape of the returned documentation.

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 takes zero parameters, so there is nothing for the description to disambiguate; the schema is empty and fully covered. Baseline 4 applies, with no penalty warranted.

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 enumerates the content this tool surfaces (inputs with units/ranges/defaults, outputs, assumptions, tables), which implies a documentation-returning tool, but it never states a verb such as "returns" or "describes". Against the sibling `calculate`, the reader must infer that this is the read-the-docs counterpart rather than the computation itself.

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?

There is no statement of when to call this instead of `calculate`, nor any prerequisite or ordering guidance (e.g. call before calculating to learn the input format). Usage is only implied by the tool name.

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