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

Annotations already declare readOnly, idempotent, non-destructive, open-world, so safety is covered. The description adds genuinely useful behavior: it discloses that client-side apps are rendered in a real browser (implying a heavier, more complete scan) and enumerates what the run produces (score, prioritized issues with why/how, AI readiness, key facts). Auth, rate limits, and failure modes are not mentioned.

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?

Front-loaded with the core action, followed by returns, a notable behavior note, and the routing hint. Sentences are purposeful, though the output enumeration is somewhat list-like and could be tightened.

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?

There is no output schema, so the description must describe returns, and it does so concretely (score, issues, AI readiness, key facts). Combined with the browser-rendering note, an agent has enough to call it correctly, though performance/cost expectations for the browser render are left implicit.

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?

With a single parameter at 100% schema coverage, the schema already fully documents the url. The description adds only the implicit 'public' constraint, which is marginal param-level value; baseline 3 applies when the schema carries the load.

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 and resource ('scan one public web page') with a clear scope (SEO and AI visibility), and the 'one public web page' framing helps separate it from scan_html. It does not name sibling tools (scan_html, deep_audit, check_ai_visibility) directly, so differentiation rests on the scope phrase rather than explicit routing.

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?

Gives an explicit entry-point heuristic: 'Use this first for any question about how a page performs in Google or AI search.' That is strong when-to-use guidance, but it offers no when-not-to-use or named alternatives for narrower checks (OG tags, schema, readability).

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