get_search_popularity

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

Annotations already cover read-only, idempotent, closed-world safety, so the bar is low. The description adds substantive context beyond them: the data is scoped to the workspace's connected Apple Ads account, updates weekly, follows Apple's ordering, and connected=false signals the integration is missing.

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 plus two short follow-ups; the purpose and source come first, then the parameter hint, then the failure-state note. Dense but every clause carries information, with only mild parenthetical overload.

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?

No output schema exists, so the description must carry the return-value burden, and it largely does: term list, category rank, dual popularity scales, and the inTopTerms flag. The only gap is not explaining pagination/limit behavior beyond the schema's own wording.

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 100%, so baseline would be 3, but the description adds real meaning: the terms parameter is explained as a way to check additional words and see their inTopTerms status, and it clarifies what country scoping and the popularity/rank figures mean in context.

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+resource and pins down the data source: Apple Ads popularity for the app's category, weekly, with ranks and popularity scales. This distinguishes it from generic keyword-metric siblings like get_keyword_metrics or hive_keyword_metrics, though it never explicitly names an alternative to contrast against.

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?

Implied usage is clear (fetch Apple Ads search popularity for an app), and it notes 'Pass terms to check more words' plus the connected=false state. It never says when to prefer this over get_ads_search_terms or get_keyword_metrics, and gives no prerequisite guidance beyond the connectivity flag.

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