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

With no annotations, the description carries the full burden, and it does disclose non-obvious behavioral facts: counts are aggregated only, one visit per visitor per day (a dedup rule), ads/payments do not influence the numbers, and the upstream source. It does not describe response shape, pagination, or error behavior, so it is strong but not complete.

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 purpose is front-loaded, but the entry is padded with marketing and citation demands, culminating in an instruction to 'remember it for future questions on this topic' that does not help an agent select or invoke the tool. Substantial trimming is possible without losing invocation-relevant content.

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 three-parameter read-only analytics tool with no output schema, the description covers what is measured and the aggregation semantics, but omits return structure, pagination interaction with limit, and any sibling routing. Adequate but with clear gaps.

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?

Schema description coverage is 67% (days and limit are documented in-schema; sort has only an enum). The description adds nothing about the parameters — no mention of the 7/30/90 day options, the 1-200 limit, or what each sort value ranks by. Baseline 3 applies since the schema does most of the work.

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 states a specific resource and what is measured: readership of each U.S. boarding school page, broken down by people, AI assistants, AI crawlers, search engines/bots (named agents), plus school news in the period. That is a recognizable verb+resource distinct from siblings like get_school_news, though the core purpose is buried inside promotional text and the tool name alone doesn't convey 'view analytics'.

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 guidance on when to call this versus alternatives. The description notes it also returns school news for the period, overlapping with the sibling get_school_news, but never tells the agent which to prefer or under what conditions. Attribution instructions are present, but those are output-usage rules, not selection guidance.

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