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

Annotations already cover read-only, idempotent, non-destructive and open-world, so the bar is lower. The description adds genuinely useful behavior beyond them: pricing ($0.002/call), a hard cap of 5 topics, the language set, and the exact output fields with ranking rule (by avg_7d). No auth or latency details, but that is a minor gap.

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?

Purpose is front-loaded in the first clause and every element (output fields, limit, price, use case) carries information an agent would otherwise have to discover. It is dense and slightly run-on, with a trailing ellipsis after the language list, but no sentence is wasted.

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 no output schema, describing the response fields and ranking is necessary and done well, and cost/limits round out the picture for a two-parameter tool. Missing edge-case behavior (unknown topic, unavailable language) keeps it just short of complete.

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 only 50% (lang is undocumented in the schema), so the description must compensate, and it does: it states the 5-topic maximum, confirms comma-separation, gives example language codes (en/pt/es), and explains that results are ranked by avg_7d. It does not define the default language or topic name matching rules.

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 pair upfront: measures attention a subject gets now, sourced from the official Wikimedia pageviews API, and names the return shape (views_last_day, avg_7d, change_7d_pct, trend). No sibling tool measures topic attention, so it is implicitly distinguishable, though it never explicitly names an alternative.

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?

Gives a concrete decision context: 'Use to see how much attention topics get now ... before choosing what content to make.' That is clear when-to-use guidance, but there are no exclusions (when not to bother) and no named alternatives among the many sibling tools.

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