ai-visibility

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

No annotations are provided, so the description carries the full burden. It discloses the three behaviors performed, including nuanced details like testing whether readable text ships without JavaScript, which goes beyond the schema. It does not mention network side effects, rate limits, or unreachable-site behavior, but the read-only 'check' semantics are reasonably transparent.

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 one front-loaded sentence that states the core purpose first, then uses a colon and a compact list for the concrete checks. Every phrase contributes; there is no redundancy, filler, or repetition of schema details.

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?

With a single simple parameter and no output schema, the description gives enough information to invoke the tool and understand the high-level return categories. A minor gap is that it does not describe the exact return shape or edge-case behavior (e.g., unreachable domains, missing robots.txt), but for a one-parameter check tool this is adequately complete.

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 fully documents the single url parameter with an example format ('example.com or https://example.com'), so the baseline is 3. The tool description adds little parameter-specific meaning beyond the schema, though the overall purpose reinforces that the URL identifies the site being checked.

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 ('Check'), a clear resource ('a site's AI search visibility'), and enumerates three concrete diagnostic outcomes: allowed AI crawlers, JS-free readable homepage text, and llms.txt existence. This clearly distinguishes it from the sibling generation/linting/validation tools.

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 'check' framing and the enumerated checks make the intended use clear: use this tool when you want a broad visibility assessment of a site. It does not explicitly name sibling tools or state when not to use them, but the context is strong enough to route an agent correctly.

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?

No annotations are provided, so the description carries the full burden. It mentions it uses 'real pages and sitemap' but does not disclose side effects, permissions, rate limits, or how the generated file is returned. The behavioral information is minimal and leaves much to inference.

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, efficient sentence with no fluff. It front-loads the core action and source, and every word adds value. This is a model of conciseness.

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?

Without an output schema, the description should explain what the tool returns or does with the generated file, but it does not. It also omits any context about the optional credit parameter. The description is too sparse to fully prepare an agent for correct invocation.

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 both parameters (url and credit) with 100% coverage. The tool description adds context that the URL is for a site and that generation relies on sitemap, which is helpful but not critical. The baseline of 3 applies because the schema does most of the work.

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 clear, specific verb ('Generate') and resource ('an llms.txt file') with a source ('a site's real pages and sitemap'). This distinguishes it from sibling tools like check_site, lint_robots_txt, and validate_llms_txt, which are about validation and checking rather than generation.

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 implies the tool is for generation, but it does not explicitly state when to use it over siblings or provide any exclusions. An agent can infer its purpose, but there is no direct guidance on choosing this tool versus validate_llms_txt or check_site.

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?

With no annotations, the description carries the burden. It does disclose a live-fetch behavior and a direct-text mode, which implies read-only linting rather than modification. However, it does not describe output format, error behavior, or what happens if both parameters are supplied, leaving some behavioral traits implicit.

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?

A single sentence that front-loads the main purpose and then gives the two invocation modes. There is no filler and every clause adds useful 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?

For a simple tool with two optional parameters and no required inputs, the description covers purpose and invocation modes adequately. Minor gaps include not describing the return value and not explicitly stating precedence when both params are provided, but the schema already hints at 'instead of fetching url', so the overall context is sufficient.

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%, so the schema already documents both parameters well. The description mostly restates the schema's 'fetch' and 'directly' semantics without adding meaningful new parameter-level detail, 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?

The description states a specific verb ('Lint'), a specific resource ('robots.txt'), and a specialized scope ('AI-crawler-specific mistakes'). This clearly distinguishes it from sibling tools like validate_llms_txt and check_site.

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?

It gives clear invocation guidance: pass url to fetch live, or pass robots_txt to lint pasted text directly. It does not explicitly name when-not-to-use alternatives or exclusions, so it stops short of a 5, but the intended usage context is unambiguous.

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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It clearly indicates validation against the spec, and the schema adds that the URL is fetched, but it does not disclose the output format or whether any side effects occur. This leaves some ambiguity about what an agent should expect after calling the tool.

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 short sentence with no filler. It front-loads the action and resource, and every word contributes to the meaning.

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?

The interface is simple with one well-documented parameter, so the description is mostly adequate. However, with no output schema and no annotations, an agent must infer what a validation result looks like; a brief note about the return value would make the tool fully self-explanatory.

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 single 'url' parameter is fully described in the schema ('A site whose /llms.txt should be fetched and validated'), so the description adds little beyond confirming that the operation targets an existing llms.txt. With 100% schema coverage, 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?

The description uses a specific verb ('Validate') and resource ('existing llms.txt') against a defined standard ('the spec'), which clearly distinguishes it from siblings like generate_llms_txt and lint_robots_txt. An agent can immediately understand what the tool does and what it is not.

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 word 'existing' implies this is for llms.txt files that are already present, which differentiates it from generate_llms_txt. However, it does not explicitly state when to choose validate_llms_txt over check_site or lint_robots_txt, nor does it mention exclusions or prerequisites.

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