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

Annotations already mark it read-only, idempotent, and non-destructive, and the description adds meaningful behavioral detail: it never fetches external data, never triggers payment or paid fallback, and abstains when evidence is ambiguous. It also discloses the evidence sources it relies on, which goes beyond the structured 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?

Two terse sentences front-load the free/no-key status and then state the core action, input constraints, abstention behavior, and no-fetch/no-payment guarantee without repetition. Every phrase earns its place.

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?

For a simple, read-only analysis tool with an output schema, the description covers input limits, no-fetch/no-payment behavior, and ambiguity handling. It does not explicitly state the role of pageUrl, but the schema example and output schema fill most remaining gaps.

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 0%, so the description carries the burden. It identifies the main input as JSON-LD HTML and hints at the optional pageUrl through 'canonical evidence', but it never explicitly explains the html/pageUrl parameters or which one is required. The inline example helps, but the description itself leaves pageUrl under-specified.

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 names a precise task: identify the main Product or ProductGroup from supplied JSON-LD HTML, and lists the evidence signals used (identity, mainEntity, canonical) plus an abstention policy. This clearly separates it from sibling preview tools such as offer_preview and pack_preview. The verb 'identify' plus the resource scoping makes the purpose unambiguous.

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 states it operates on supplied data only, with no fetch, payment, or paid fallback, and that it is free and keyless, which tells an agent when this tool is appropriate. It also provides a decision rule to abstain on ambiguity. It does not explicitly name sibling alternatives or exclusion conditions, but the context is clear enough.

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