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

Annotations already declare readOnlyHint=true, idempotentHint=true and destructiveHint=false, so safety is covered. The description adds a non-obvious data-interpretation caveat ('Missing coverage is not zero') that prevents the agent from misreading absent data as zero, which is real value beyond structured fields. It still says nothing about pagination despite a cursor parameter existing.

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?

Two short sentences, front-loaded with the resource and immediately listing the selectable views, then closing with the key caveat. No filler, though the view list is dense enough that it could be tied more explicitly to the enum values.

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?

With 12 parameters, no output schema, and 0% schema coverage, the description leaves most parameters and the pagination model undocumented. It covers the view dimension and one interpretation caveat but is far short of what an agent needs to call this 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?

Schema description coverage is 0% across 12 parameters, so the description must carry the load and largely does not. It gestures at the view enum values ('summary, per crawler, log coverage, individual requests') but never explains limit, range, cursor, bot_id, folder, status, start_date, end_date, verification, or resource_class.

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?

States a specific verb and resource (reads AI crawler requests from server logs) and enumerates the four view modes, so the agent knows exactly what the tool returns. It does not, however, name or distinguish itself from the nearby sibling read_ai_crawlability, leaving that routing 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?

The mapping of views to use cases (summary vs per crawler vs coverage vs individual requests) implies how to pick granularity, which is genuine usage signal. But there is no explicit when-to-use / when-not guidance and no reference to alternative tools such as read_ai_crawlability or read_ai_referrals.

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