alice

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

Annotations declare readOnlyHint, openWorldHint, and destructiveHint false. The description adds that it performs a live check with results in about a minute, and details what the score includes (crawler access, server rendering, structured data, fixes). This provides valuable behavioral context beyond the annotations without contradiction.

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 a single sentence that efficiently packs the purpose, process, and output details. It is front-loaded with the core purpose and avoids unnecessary fluff, making it easy for an agent to parse.

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 tool's complexity and the presence of an output schema, the description covers what it does, how it works (live check, timing), and what it returns (score, factors). It provides sufficient context for an agent to decide when to use it, with no critical missing information.

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 description coverage is 100%, so the schema already fully documents both parameters (url and full). The description does not add extra parameter details, but this is not necessary given the high coverage. Baseline 3 is appropriate.

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 checks AI visibility and readability for a URL, with a specific verb and resource. It differentiates from the sibling by focusing on a single site, though it does not explicitly mention the comparison tool. The purpose is unambiguous.

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 explicitly lists scenarios where this tool should be used, such as when users ask about AI mentions, readability, or visibility audits. It provides clear context but does not mention when not to use it or alternative tools, which is a minor gap given the sibling tool exists.

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

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

Annotations already declare readOnlyHint=true and openWorldHint=true, covering safety and external dependency. The description adds specific behaviors: scanning 2-4 URLs, ranking by AI visibility score, and reporting on crawler blocking, server rendering, and structured data. This goes beyond the annotations without contradicting them, though it doesn't detail response structure (covered by output schema).

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 compact—two sentences, zero filler. The core purpose is front-loaded, followed by usage context. Every clause earns its place, and the differentiation from the sibling is embedded naturally.

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 one simple parameter, a rich output schema, and annotations covering safety and open-world behavior, the description is complete. It tells the agent what the tool does, when to use it, and the key behavioral outputs, leaving nothing essential missing.

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% (the urls array is fully described with min/max items). The description adds value beyond the schema by instructing the agent to put the user's own site first and stating that results are returned ranked by score, which affects how the parameter should be ordered. This is helpful supplementary meaning.

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 uses a specific verb ('Compare') and resource ('how visible several websites are to AI answer engines'), clearly distinguishing it from the sibling check_ai_visibility (which likely checks a single site). It also enumerates the concrete outputs: ranking, AI crawler blocking, server rendering, and structured data readiness, making the purpose unmistakable.

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 explicitly states when to use the tool ('benchmark their site against competitors' or 'asks why a competitor gets recommended by AI assistants') and implies the alternative (single-site check) when a single URL is involved. This gives clear decision criteria and routes the agent appropriately.

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