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

The description goes beyond the annotations by stating that the results are 'derived from bytes fetched live — no estimates' and enumerates the concrete measures performed (robots.txt, JS rendering, structured data fields, meta, sitemap). It communicates non-mutating behavior and the reliability characteristics of the output. It does not mention rate limits or response size, but for a read-only diagnostic tool this is strong transparency.

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?

Every sentence earns its place: the first sentence states the output and purpose, the second explains the measures, and the last tells the agent what input to provide. The especially thorough list of measured fields is informative but not overly verbose for the including a highly detailed tool.

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 a single required parameter, no output schema, and no sibling tools, the description is sufficiently complete: it states what the tool returns, the scope of checks, the data source (live bytes), and which input maximizes usefulness. The agent has everything it needs to call the tool correctly and interpret the result.

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 description coverage is 100%, so the parameter is already fully documented with type and examples. The description adds useful extra meaning on top of the schema by indicating that product URLs yield the best result, enhancing an already-covered parameter without needing to compensate for a gap.

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 uses a specific verb ('checks') and a clear resource (online store pages), then expands on it by naming the deliverable ('ready-to-paste JSON-LD Product snippet'). It differentiates the type of input ('storefront domain or direct product URL') while clarifying that 'a product page gives the most useful result.'

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 gives explicit practical guidance on what to provide ('Give it a storefront domain or a direct product URL') and which input yields the best result. There are no sibling tools to compare against, so it cannot name alternatives, but the usage context is clear and actionable.

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