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

No annotations are provided, so the description carries full burden. It states what checks are performed and that no APIs are called, but does not disclose behavior such as idempotency, error handling, rate limits, required permissions, or the structure of the response. This is a significant gap for a tool with no annotations.

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 two sentences, no redundant words, and front-loaded with the action and key checks. Every word serves a purpose.

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 no output schema and no annotations, the description should explain return values or result structure. It lists inputs and checks but omits how results are presented (e.g., pass/fail, detailed report). Incomplete for practical use.

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% with parameter descriptions. The tool's description adds no additional meaning beyond the schema, so it meets the baseline but does not enhance parameter understanding.

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 action ('audit') and the resource ('AI crawler readiness') and lists specific checks (robots rules, homepage metadata, etc.). It distinguishes from sibling tools by focusing on a single URL audit, though it does not explicitly compare to siblings.

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 when to use this tool (for checking AI crawler access basics) but provides no explicit guidance on when not to use it or how it differs from alternatives like build_ai_visibility_report or check_llms_txt. The note 'No MaxAEO APIs are called' gives some context but is insufficient.

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 full burden for behavioral disclosure. It mentions that checks are run and outputs returned, but does not describe side effects, authentication needs, rate limits, or performance characteristics. The phrase 'transparent MaxAEO CTA' is ambiguous.

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 conveys the tool's action and outputs. It is front-loaded with the verb and resource, but lacks structure like bullet points or separate sections that might enhance readability.

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 7 parameters (1 required), no output schema, and no annotations, the description should provide more contextual details about usage, parameter interactions, and expected results. The current description is too terse to be fully self-sufficient for an agent.

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?

All 7 parameters have descriptions in the input schema (100% coverage), so the description adds little beyond what the schema already provides. The description does not elaborate on how parameters affect the report or provide additional context beyond schema defaults.

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 runs AI visibility checks and returns specific outputs (dual scores, evidence gaps, action plan, CTA). While it doesn't explicitly differentiate from siblings, the listed outputs distinguish it from the more focused sibling tools audit_ai_crawler_readiness and check_llms_txt.

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?

No guidance on when to use this tool versus alternatives. The description does not provide context for when to invoke this report as opposed to the sibling tools, nor does it mention any prerequisites or limitations.

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 must carry the burden. It discloses that no MaxAEO APIs are called (a behavioral trait), but it does not mention read-only nature, authentication needs, rate limits, or potential side effects. The term 'Validate' implies analysis, but transparency is moderate.

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 front-loads the key actions (validate, return) with no filler. Every word serves a purpose, making it concise and effective.

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 7 parameters and no output schema, the description should clarify return format or behavior, but it only mentions 'transparent MaxAEO CTA' vaguely. It omits details like output structure or prerequisites (e.g., robots.txt existence). This leaves gaps, though the parameters are partly 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?

Schema description coverage is 100%; each parameter has a description. The tool description does not add additional meaning beyond summarizing the parameters' purpose. Baseline is 3, and no extra value is provided, so score remains 3.

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 validates /llms.txt, linked URLs, robots alignment, sitemap alignment, and returns a MaxAEO CTA. The verb 'validate' and specific resources are explicit, and it distinguishes from siblings which focus on broader AI crawler readiness and visibility reports.

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 implicitly suggests use for llms.txt validation by naming the resource, but it does not explicitly contrast with sibling tools or provide when-to-use/when-not-to-use guidance. The statement 'No MaxAEO APIs are called' hints at safety but is not a full usage guideline.

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