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

Annotations already declare readOnly, idempotent, openWorld and non-destructive, so the safety profile is covered. The description adds a genuinely useful behavioral fact beyond that: it requires GCP service account credentials supplied via credentials_path or the GOOGLE_APPLICATION_CREDENTIALS env var, which affects whether the call can succeed.

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?

Three tight sentences with zero padding: purpose first, then the value proposition, then the credential prerequisite. Front-loaded and each sentence earns its place.

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?

An output schema exists so return values need not be described, and all seven parameters are covered by the schema. The description supplies purpose, value and auth prerequisite, leaving only sibling routing (vs signals_bing_gap) unaddressed.

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 100%, so every parameter including the engine enum and date formats is already documented in the schema. The description only restates the credential source and the GSC/citation join, adding little semantics beyond what the schema provides. Baseline 3 is appropriate.

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: it joins GSC performance with citation data and surfaces queries where the domain ranks in Google but is not cited in AI. The phrase 'the closest editorial wins' adds a concrete framing of the output. It does not name the obvious sibling signals_bing_gap, so differentiation is left 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 value framing ('closest editorial wins') implies the scenario where this is useful, but there is no explicit when-to-use or when-not, and no reference to the near-twin signals_bing_gap. The usage context is implied rather than spelled out.

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