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

Annotations already declare readOnlyHint, idempotentHint and non-destructive, so safety is covered. The description adds behavior beyond that: the values are aggregated across all shops and the window is a rolling 30-day comparison, which tells the agent what it will actually receive. No output schema exists, so this return-shape disclosure carries real weight.

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 sentences, no filler, with the data description front-loaded before the use case. Every clause 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?

With no output schema, the description usefully enumerates the returned metrics, and annotations cover the safety profile, leaving little ambiguity for a simple two-parameter read. Minor gap: nothing about the timezone/granularity of the daily series.

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 both parameters documented including the 7-365 range and the source of product_key, so the schema does the heavy lifting. The description's only added nuance is 'all shops together', which is an aggregation note rather than parameter meaning. Baseline 3 applies.

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 specific resource (lowest daily total price of a product over time) plus the exact aggregates returned: lowest price ever and change versus 30 days ago. This is distinguishable from compare_prices/search_products, which the sibling list shows are lookup tools rather than historical aggregation.

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 frames the use case ('is this a good moment to buy?'), giving clear context for when to call it. It stops short of naming when-not-to-use or pointing to a sibling alternative for other price questions, so it lands below a 5.

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