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

Annotations already establish readOnly, idempotent and non-destructive behavior, so the bar is lower. The description adds real value beyond that: it names the connected data sources, states that each recommendation carries a source plus a suggested action, and explains the automatic Ads-account fallback when customer_id is empty.

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 opens with the core value proposition and then lists the concrete opportunity types; the trailing customer_id sentence is operationally useful rather than filler. Dense but every clause carries information.

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 an output schema present, the description need not document return shape, and it still sketches what each recommendation contains. The only real gap is the undocumented 'days' parameter, which an agent needs in order to call the tool with the right reporting window.

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%, so the description must compensate. It explains customer_id's empty-string default behavior (active Ads account selected automatically), but says nothing about 'days' — neither its default of 28 nor what window it controls. Half the parameters are left to inference.

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 gives a specific verb (derives prioritized, actionable recommendations) plus a concrete scope: cross-channel opportunities drawn from Search Console, Ads, GA4 and Business Profile. It enumerates the exact signals it surfaces, which makes it distinguishable in substance from marketing_overview or list_recommendations, though it never names those siblings explicitly.

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?

Usage is implied by the content ('opportunities', 'what to do'), and the note about customer_id auto-selection tells the agent it can be called with no arguments. But there is no explicit when-to-use / when-not-to-use guidance or routing against the many adjacent tools such as marketing_overview, list_recommendations or apply_recommendation.

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