Run a full audit

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

Beyond the readOnlyHint and openWorldHint annotations, the description discloses important behavioral traits: it requires a Website Auditor subscription with trial terms, it returns a scored summary plus a report link, and it instructs how to handle the name_warning caveat. It also reveals that a guessed business_name is scored as confirmed, which is a nuanced behavior an agent needs to know.

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 densely informative yet efficiently arranged: purpose, usage triggers, output summary, caveat handling, subscription details, and fallback alternative. Every sentence earns its place, with no fluff or redundancy. The single paragraph flows logically from what to when to how.

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?

Despite having no output schema, the description tells the agent what to expect ('a scored summary across categories and a link to the full report') and covers caveats, subscription requirements, and an alternative path. Combined with the rich schema and sibling context, it is fully self-sufficient for correct invocation and response handling.

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?

Although the schema covers 100% of parameters, the description significantly enriches semantics for business_name and business_location. It explains the consequence of omitting business_name (auto-detection with unverified flag) and warns that a guessed name is scored as confirmed, which is critical for data integrity. Similarly, it clarifies how business_location affects detection and scope, adding value far beyond the 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 opens with a specific verb+resource+scope: 'Run a full one-time audit of a website — AI visibility plus SEO, security headers, broken links, and performance.' It clearly distinguishes the tool from siblings like get_ai_visibility, which only returns the AI-visibility number, by emphasizing the complete multi-category report.

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 it ('Use this when someone asks to audit, scan, check, or review a website's health or SEO, or wants a complete report rather than just the AI-visibility number') and provides a clear alternative for non-subscribers: 'call get_sample_audit first.' It also covers subscription prerequisites, making the decision boundary precise.

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