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

With no annotations, the description carries the behavioral burden and does well: it discloses cost per call, how payment works, that failed/empty calls are free, and what the response contains. It omits minor details like rate limits or auth key handling, but the key behaviors are covered.

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?

Three sentences, each earning its place: purpose and syntax, response shape, and cost/failure semantics. The text is front-loaded with the main action and free of filler.

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?

For a one-parameter tool with no output schema, the description covers everything needed: how to form queries, what fields to expect, per-call cost, and the free-on-failure condition. The agent can invoke it correctly without more context.

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 describes the single query parameter with an example, and coverage is 100%. The description adds valuable semantics by listing the exact advanced operators an agent can use, enriching the bare word 'query' with concrete syntax.

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 opens with a specific verb and resource: 'Live X/Twitter search for AI agents.' It further disambiguates by listing supported search syntax and result fields, distinguishing it from siblings like x_profile or x_digest.

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 establishes a clear use case: live X/Twitter search with advanced query syntax, so an agent knows when to call it for fresh posts. It does not explicitly name alternatives or state when not to use it, but the context is clear enough.

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