AI shopping readiness

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

With no annotations, the description carries the burden of disclosure. It clearly states the tool inspects published structured data and cannot see private feeds, which is a key limitation. It also names what it evaluates (schema completeness, price, availability, attributes), giving a solid behavioral overview.

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?

Three sentences, each earning its place: the first states purpose, the second gives usage context, and the third describes a limitation. The description is front-loaded and concise without unnecessary fluff.

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?

Given no output schema, the description explains what the tool checks and its limitation, which sets appropriate expectations. It doesn't describe return format, but the scope of analysis is clear. For a diagnostic tool with one parameter and clear use cases, this is reasonably complete.

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 parameter url is fully described in the schema with examples (example.com or https://example.com), achieving 100% schema coverage. The description adds no extra parameter-level detail beyond what the schema provides, so the baseline score of 3 is appropriate.

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 clearly states the tool checks whether AI shopping agents can find, understand, and recommend products, focusing on schema completeness, price/availability signals, and attributes. This specific verb+resource scope distinguishes it from sibling tools like offpage_gaps or crawler_watch.

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 says to use for e-commerce sites, especially Shopify, when products never surface in AI recommendations. Also provides exclusion: it cannot see privately submitted merchant feeds, which helps avoid misuse. No explicit alternatives are named, but the when-to-use guidance is strong.

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