Get trending topics (coming soon)

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

The description richly discloses behavior beyond the annotations: the tool is not public yet and returns an error, calls are billed per returned article, failed/no-data lists are free, data comes from Wikimedia Pageviews with rounding differences, there is a one-day publication delay, and maxTotalChargeUsd caps spending. This far exceeds what the readOnlyHint and destructiveHint annotations convey.

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?

The description is long but every sentence carries useful information: availability status, data scope, source, use cases, defaults, pricing, and execution details. The coming-soon caveat is front-loaded. A slight structural split into availability, behavior, and billing would improve readability, but the density is justified.

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?

Despite having no output schema, the description covers what is returned (rank, views, one-line description), default behavior, error cases, cost, API source, and execution constraints. For a tool with seven optional parameters and billing implications, this is unusually complete and leaves little ambiguity for an agent deciding whether and how to call it.

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 the schema already documents each parameter. The description adds meaningful semantics beyond the schema: the default day is the latest published day, the English edition is listed if neither country nor project is provided, and maxTotalChargeUsd acts as a hard spend cap. This justifies a score above the baseline of 3.

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 clearly identifies the tool's purpose: listing most-read Wikipedia articles by country and/or language edition, with rank, views, and descriptions. It is specific about the data source and scope, but it does not explicitly distinguish itself from the sibling tool 'get_topic_trends', so differentiation relies on context rather than a direct statement.

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 concrete use cases ('news and social monitoring, content ideas, or 'what is trending in Japan today?') and explains the default behavior when no trendingCountries or trendingProjects are provided. However, it does not explicitly state when to use this tool instead of an alternative or when not to use it, aside from the implied 'coming soon' unavailability.

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