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

The description goes far beyond the sparse annotations (readOnlyHint:false, destructiveHint:true) by explicitly stating: 'No outbound actions or private CRM access,' 'Returns a draft for human review,' 'Payment requires explicit wallet authorization,' and 'If no public domain is supplied, identify that missing evidence instead of inventing an audit.' It also discloses limitations on claiming ranking/traffic measurement and separates observed HTML signals from business assumptions. This fully discloses behavioral traits without contradicting the 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 lengthy but every sentence adds substantive value: it covers purpose, adaptation, risks (heuristics, missing domains), return type, side effects (payment), and output structure. It is front-loaded with the core action, then flows logically through constraints and disclaimers. It could be slightly more concise, but it avoids redundancy and remains focused.

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 description is comprehensive in behavioral and output expectations, covering return format, missing-domain handling, and pricing. However, it fails to explain the input parameter semantics, which is critical when schema coverage is 0%. Since the tool has a nested object parameter and no output schema, the agent needs to know what to put in 'task' and how to handle optional parameters. This incomplete parameter guidance lowers the score.

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 0%, so the description must compensate, but it does not explain the parameters. The only required parameter is 'input' (an object with a required 'task' string), yet the description never states what 'task' should contain (e.g., the URL or domain to audit). Optional parameters like result_expires, idempotency_key, result_signature, and payment_signature are mentioned only indirectly via price/payment caveats, but their exact meaning and usage are left to inference. This is a significant gap given the lack of schema descriptions.

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 opens with a specific verb and resource: 'Audit the buyer's public website using the audit tool' and specifies the output as 'an evidence inventory followed by conditional improvement options.' This clearly distinguishes the tool from siblings like seo_audit (which likely focuses on SEO metrics) and content_gap (which targets content gaps) by emphasizing evidence-based, conditional recommendations rather than generic audits.

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 provides strong contextual guidance on when to use the tool: it should be used for auditing a website and producing evidence-based options, with explicit instructions to adapt to the site's purpose (e.g., a documentation example may need no SEO expansion). It also cautions against universal checklists or assuming measurement. However, it does not explicitly name alternative tools or state when not to use it, so it falls short of a clear 'use X instead' directive.

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