check_ai_visibility

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

Adds meaningful context beyond annotations: cost (10 quota units/call), free-tier limits (3 checks/month), platform availability constraints (Perplexity and Gemini not supported), and return format details. No contradiction with annotations; read-only is consistent with readOnlyHint=true.

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?

The description is appropriately sized and front-loaded. Every sentence adds value: purpose, use cases, cost, return JSON, alternatives, and parameter details. No filler; well-structured and easy to scan.

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 2 simple params, no output schema, and strong annotations, the description covers all necessary context: purpose, usage, parameters, return values, cost, availability, and alternatives. It is complete and leaves no critical gaps for an agent to invoke the tool correctly.

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 has 0% description coverage, so the description fully compensates. It explains domain format ('no https://, no www') and platform allowed values ('chat_gpt' or 'google') with default and exclusions, adding essential meaning beyond the bare 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 states a specific verb+resource+scope: 'Check how many times a domain is cited in AI-generated answers on a given AI platform.' It also distinguishes from siblings by explicitly naming citation_leaders and analyze_citation_trend as alternatives for different needs.

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?

Provides explicit when-to-use ('is my brand/domain visible in AI search') and when-not-to-use alternatives ('Use citation_leaders instead...', 'Use analyze_citation_trend instead...'). This is exactly the level of guidance expected.

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