automation_metrics

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

With no annotations, the description carries the burden of behavioral disclosure. It does disclose that the token count is an estimate, but it does not state whether the call is read-only, what 'recent' means, or whether metrics are cumulative or scoped. This is minimal but not misleading.

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?

A single, front-loaded sentence states the returned quantities without filler. Every word contributes.

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?

The tool is simple with one optional parameter and an output schema, so the description does not need to explain return shape. The only noticeable gaps are the undefined 'recent' window and unspoken limit semantics, which are minor for a low-complexity metrics tool.

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% and the description does not mention the limit parameter at all. The name and default imply it caps the number of returned metric records, but the tool description adds no meaning beyond the schema, so the agent must guess how limit affects the result.

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 a concrete action and resource: it returns recent latency, response size, and token estimates for browser-side tools. This is enough to know what the tool does, but it does not explicitly differentiate it from sibling profiling/metrics tools such as ui_profile.

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 use this tool versus alternatives, no exclusions, and no context such as checking performance before a task or after a browser action. The only hint is the tool's stated purpose, which leaves the selection condition to the agent's inference.

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