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

Annotations already cover safety (readOnly, openWorld, non-idempotent), yet the description still adds real behavioral context: it reveals the extraction sources (JSON-LD, microdata, OpenGraph), respects robots.txt, is not billed when no structured product data is found, and states the price/payment mechanics (USDC, x402 or prepaid credits, free trial).

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?

Purpose and field list are front-loaded in the opening clause, and the pricing/billing details follow in order of relevance. The single long sentence is dense but every clause (fields, sources, robots, billing) 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?

An output schema exists, so return-value documentation is unnecessary, yet the description still enumerates the output fields and covers the billing/non-charge behavior an agent needs before calling. Nothing material is missing for a one-parameter extraction tool.

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% with a single 'url' parameter, so the schema already carries the semantics. The description adds only the implicit constraint that the URL must be a public product page, which is the expected baseline, not extra value.

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+resource ('Product and price from any public product page') and enumerates the extracted fields, so an agent knows exactly what comes back. It gestures at the sibling product-ai via '(see /product/ai)' rather than clearly differentiating, which keeps it just short of a 5.

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?

Usage is implied by scope ('any public product page') and the non-charge condition hints that product-ai is the fallback when no structured data exists, but the when-to-use/when-not guidance is only oblique and never names product-ai explicitly as the alternative.

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