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

No annotations are provided, so the description carries full burden. It describes the comparison against 'current retail across tracked specialty shops' and the return values, but does not disclose limitations like data freshness, scope of shops, error handling, or behavior when price is omitted. This is adequate but incomplete.

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?

The description is two effective sentences plus a usage guideline sentence. Every sentence is meaningful and front-loaded, with no wasted words.

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?

The description covers the return values (verdict, price band, where to buy) despite no output schema. It mentions all parameters. Missing details about error cases or data freshness prevent a perfect score, but overall it is sufficiently complete for the tool's niche.

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 schema already explains each parameter. The description adds value by listing example products for the niche parameter and clarifying that price is 'the asking price you're seeing'. This enriches understanding beyond the schema.

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 if a hobby item's price is fair or scalped by comparing against retail prices. It specifies supported niches with examples, distinguishing it from sibling tools like check_in_stock or find_settlements.

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 explicitly says 'Use when an agent or user wants to know if a... item is overpriced.' This provides clear context for when to use. It does not explicitly state when not to use or list alternatives, but the context is sufficient given sibling tool diversity.

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