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

Beyond the readOnly/idempotent annotations, the description discloses useful behavioral detail: results come per engine, are expressed as 'k of n answers', include market and date plus earlier measurements of the same questions, and that a percentage is only shown from 10 answers. The sample-size threshold is exactly the kind of caveat an agent would otherwise misreport; only pagination/limits are unaddressed.

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?

One front-loaded sentence opens with the core question ('Whether AI assistants named your site') and then qualifies it. It is dense but every clause carries information; the engine enumeration is the only mildly padded segment.

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 shape needn't be spelled out, and the description still covers sample-size gating, comparison to earlier measurements, and per-engine granularity. What remains thin is guidance on choosing this over the other AI-visibility siblings.

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% and the single `site` parameter already documents domain format, optionality, and the multi-site selection behavior. The description adds nothing about the parameter, so the baseline of 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 precise verb-and-resource pair: reads whether AI assistants named your site in the latest Goppa measurement, broken out per engine (ChatGPT, Gemini, AI Overview, AI Mode, Perplexity). It does not explicitly name or disambiguate against close siblings like get_ai_answers, get_ai_sources, or get_ai_traffic, so the agent must infer the split from the data it says it returns.

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?

Usage is only implied: 'latest Goppa measurement' signals this reads existing measurement data rather than running one (run_ai_measurement). There is no explicit when-to-use, when-not-to-use, or statement of which sibling answers which adjacent question.

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