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

Annotations already declare the tool as read-only and idempotent. The description adds behavioral context by explaining the filtering mechanism and output fields (trend name, search query, rank). It provides example WOEIDs, enhancing transparency beyond annotations.

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?

Two compact sentences: the first states the primary purpose and the second adds filtering details and examples. No unnecessary words, front-loaded for quick understanding.

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?

Given the simple tool with one optional parameter, read-only annotations, and an output schema (implied by context), the description covers all essential aspects: purpose, filtering method, return fields, and common WOEID values. No gaps for typical usage.

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?

The schema already provides full coverage (100%) for the single parameter woeid, including examples. The description repeats the filtering purpose and examples but adds minimal extra meaning beyond the schema.

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 states the tool gets current trending topics on Twitter/X, specifies filtering by WOEID, and lists return fields (trend name, search query, rank). It distinguishes from siblings like twitter.tweets.search and twitter.users.* through the specific focus on trends.

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 implicitly indicates when to use (to get trending topics) but does not explicitly state when not to use or contrast with alternatives. It provides filter instructions but lacks guidance on alternative tools for different Twitter queries.

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