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

Goes well beyond the read-only/idempotent annotations: it states that nothing is applied live, that every change requires review/approval, that the render/JS fix is a hosting change rather than generated code, and that no engine recommendation can be promised. These are exactly the operational and expectation-setting facts an agent needs before invoking it.

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?

Purpose and usage trigger are front-loaded, followed by return shape and caveats, so the important information is easy to find. It is dense and the trailing mentionByEngine reporting instructions are somewhat tangential to invoking the tool, keeping it just short of a 5.

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, the description compensates by describing the return object structure (domain, grade, reviewRequired, proposals with id/type/title/rationale/autoApplicable/needsInput/artifact, summary). Combined with the no-side-effects guarantee and public-site scope, an agent has enough to call and interpret it correctly.

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 domain parameter already has 100% schema coverage, including the no-protocol/no-path constraint. The description adds only mild meaning ('works on any public website — no login required'), so it neither detracts nor contributes substantial parameter guidance beyond the schema baseline.

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?

States a specific verb (scan and return a reviewable plan) and resource (proposed AI-visibility fixes for a website), and enumerates the artifact types produced. It clearly differentiates itself from the sibling check_ai_visibility by being the remediation-planning step rather than the diagnostic.

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?

Explicitly sequences the tool: 'Call this after check_ai_visibility when someone asks "how do I fix it?" or "what would you change?"'. That names both the prerequisite and the user-intent trigger, leaving little ambiguity about when to choose it over the sibling diagnostic.

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