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

Annotations already cover safety (readOnly, idempotent, non-destructive, closed-world), and the description adds the genuinely non-obvious behavior: no sign-in required, and the card ALWAYS shows the example brand regardless of what is passed in. That 'input does not change output brand' trait is exactly the kind of context an agent cannot get from the schema or 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?

Front-loaded with what the tool shows, then the usage condition, then the fixed-brand caveat — a sensible order with no filler sentences. It is slightly repetitive, restating the sign-in/own-brand point twice in the final sentence, which is the only thing keeping it from 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 carries the return-value burden and does so by listing the card's contents (mention rate per engine, competitor names, sample answers). For a zero-required-parameter, read-only demo tool with full annotation coverage, nothing an agent needs in order to call it correctly is missing.

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% and the single optional 'brand' parameter is already documented, so the baseline is 3. The description goes slightly beyond by confirming the example card is returned either way and that the named brand is only echoed with a sign-in note, which clarifies why the parameter exists at all.

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 concrete verb and resource — shows a real AI visibility card for one fixed example brand (Tesla), sourced from ChatGPT, Perplexity, Claude and Google AI Overviews. It also enumerates what the card contains (mention frequency per engine, named competitors, sample answers), which clearly separates it from siblings like get_visibility or get_competitors that serve a signed-in user's own brand.

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 names the trigger ('when someone asks whether their brand shows up in AI answers and has not signed in') and the exclusion ('to check their own brand they sign in'), implicitly routing to the authenticated sibling tools. Nothing about when to pick this over get_visibility is left to inference.

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