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

Annotations cover read-only/open-world status, and the description adds real scope information the annotations do not: no posts, no recommended users, and explicitly no pagination. This prevents an agent from attempting paging or expecting content payloads. It stops short of noting rate limits or result caps.

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 dense sentences with zero filler; scope and the negative constraints are front-loaded, and the usage hint comes last. Every clause carries information.

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?

An output schema exists, so return-format explanation is not required, and the description covers scope, exclusions, and usage. For a single-parameter read tool this is essentially complete; only minor caveats like rate limiting are absent.

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?

Only one parameter and its schema description is fully documented (keyword/phrase, with exclusions for links, IDs, and pagination tokens). The description adds no format or syntax details beyond the schema, 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 verb+resource: retrieve keyword autocomplete suggestions from the X/Twitter search box. It explicitly disambiguates from siblings by naming what it does NOT return (posts, recommended users), which is exactly what an agent needs to separate it from x_search_posts and x_search_users.

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 clear usage route: the returned text feeds post search, and if an explicit search term already exists the agent should search posts directly. The alternative is described behaviorally rather than by tool name, so the routing is clear but not fully explicit.

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