Traffic, errors and speed

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

The annotations already establish that this is a read-only, non-open-world operation. The description adds valuable data semantics by warning that requests include bots and every page asset, so they are not equivalent to visitors.

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 compact and front-loaded: first the returned metrics, then the usage trigger, then an important caveat. Every sentence contributes useful information without repetition.

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 one-parameter read-only metrics tool with no output schema, the description supplies the metric set, the correct usage scenario, and the key interpretation caveat. Nothing necessary for correct invocation appears to be missing.

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 single optional 'days' parameter is fully documented in the schema with range and default. The description does not add further syntax or meaning beyond that, so the schema-coverage baseline of 3 applies.

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 names the exact metrics returned: requests, server-error rate, p50/p95 response times, and requests per day. It also distinguishes this from the sibling logs tool by contrasting 'what happened' with 'how often'.

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 concrete trigger: check this when the user says the site is slow or failing. It also explicitly routes the agent to logs for detailed event context, making the selection between alternatives clear.

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