verify_metric

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds that this hits Google again (a live external call), but omits the key behavioral outcome: what happens on a mismatch, whether a failed verification raises an error, and what tolerance_pct does to the result.

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 with an illustrative example and no filler. It is efficient, though the single-sentence brevity is part of why behavioral and parameter detail are missing.

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?

Wrong — see below.

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 coverage is 67% and the description adds no parameter meaning at all — it never mentions site, metric, expected, or tolerance_pct. The two most consequential params (expected and tolerance_pct) have no description in the schema either, so the verification-matching logic is undocumented in both places.

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 verb and resource: re-query Google to confirm a number. The example ('this page got 500 clicks') makes the intent concrete. It does not name the sibling it differs from (performance_query), so an agent must infer the distinction from the name alone.

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 usage context — verify before presenting a number — but never says when not to use it or which alternative to call instead (e.g. performance_query for exploration). The trigger condition is implied rather than stated as a rule.

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