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

With no annotations provided, the description carries the full behavioral burden. It discloses the type of information the tool provides: what was measured, when, over what population, and caveats about what the measurement cannot tell you. This is meaningful behavioral context beyond the tool's name.

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 short sentences with no wasted words. The first sentence lists exactly what content to expect, and the second provides a direct usage instruction. It is tightly structured and easy to parse.

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, stateless informational tool, the description covers the essential context an agent needs: what the tool reports and when to use it. It does not describe output formatting or return structure, but there is no output schema and the tool's purpose is simple enough that this is not a major gap.

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 100% schema description coverage, so there are no parameter semantics to clarify. The description appropriately focuses on the tool's output and usage intent rather than inventing parameter detail.

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 communicates what the tool returns: the scope and limitations of measurements on this server. It is specific enough to orient an agent, though it does not explicitly contrast itself with the sibling 'summary' or 'method' tools, so some differentiation is left to inference.

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 gives an explicit usage rule: 'Read this before quoting any number from this server.' This tells the agent when the tool is appropriate and frames it as a mandatory prerequisite for citing data. It does not name alternatives or exclusions, but the guidance is actionable and context-rich.

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