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

Annotations already cover the safety profile (readOnlyHint, openWorldHint, destructiveHint), so the bar is lower. The description still adds real value by disclosing the credit cost ('1 credit') and the returned fields (position, volume, CPC in USD), which annotations do not carry.

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 carries the resource, scope, returned metrics, cost, and safety in minimal words. No filler, no restating of the name.

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?

There is no output schema, so the description correctly describes what is returned (keywords with position, volume, CPC). Combined with complete parameter documentation and full annotations, an agent has enough to call it correctly; only the lack of explicit sibling routing keeps it short of a 5.

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%, and the schema fully documents brand, country, and competitor (including default brand and default GB country behavior). The description adds no parameter-level syntax or defaults, so the baseline 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?

States a specific resource and verb-equivalent ('competitor's biggest non-brand organic keywords') and enumerates the returned metrics, so the agent knows exactly what it gets. It implicitly separates itself from the ads siblings via 'non-brand organic,' but does not explicitly name a sibling the way the calibrating high example does.

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 description gives no when-to-use guidance, no prerequisites, and no named alternatives. It does not say how this differs from serp_snapshot or competitor_ads_* beyond the implicit 'organic keywords' framing, leaving routing entirely to inference.

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