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

The description adds useful behavioral context: it consumes a capped on-demand re-measure, runs the measurement, changes nothing else, and takes a few minutes. However, it undermines this by first saying 'queues nothing,' which conflicts with the rest of the description. This internal contradiction makes the tool's actual side effects unclear.

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 relatively short and front-loads key behavioral details, but the first sentence is confusing and seems to contradict the rest. That sentence does not earn its place and adds ambiguity rather than clarity, preventing a higher score.

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 zero parameters and no output schema, the description covers important context: trigger timing, quota consumption, async results, and the follow-up tool. However, it fails to resolve the demo-vs-live ambiguity and does not describe what the worked example response looks like, leaving gaps in completeness.

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?

There are zero parameters and schema coverage is 100%, so the description has no obligation to explain parameter semantics. A baseline of 4 is appropriate since no parameter information is missing and the description correctly avoids inventing parameter details.

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 states the intended action: 'Queue a fresh deep measurement right now instead of waiting for the weekly scan.' However, the opening sentence 'DEMO: returns a worked example of the response and queues nothing' directly contradicts that purpose, leaving the agent uncertain whether this tool actually queues a rescan or merely demonstrates the response.

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 a clear usage context: use when you need a fresh deep measurement instead of waiting for the weekly scan, and follow up by reading get_visibility again. But it does not explicitly say when not to use it, discuss plan/cap limitations, or name alternatives beyond the implied get_visibility follow-up.

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