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

Annotations already cover read-only, idempotent, closed-world and non-destructive behavior, so the description is free to add the genuinely non-obvious trait: results are split into fully-comparable rows and partial rows with missing products named, so a blank is never misread as a worse value. That is real behavioral context beyond the annotations, though error handling for invalid SKUs or out-of-range counts is unstated.

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?

Three sentences, front-loaded with the core operation, and each carries distinct information (scope, return shape, non-ranking caveat). The middle sentence is long and clause-heavy, but nothing is redundant.

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 carries the burden of explaining returns and does so: comparable rows versus separately returned partial rows with missing products named. Combined with the non-ranking caveat, an agent has enough to call it and interpret the result correctly.

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 coverage is 100% and the single parameter already documents 'Two to six part numbers or slugs', so the description's restatement of the 2-6 bound adds little. It does imply that only attributes shared across all supplied SKUs are compared, which slightly enriches the meaning of the list, but the baseline of 3 applies when the schema does the heavy lifting.

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 states a specific verb and resource ('Compare two to six products') plus a precise scope: only attributes every product publishes. That scope cleanly separates it from get_product_details or search_products, which an agent can tell apart without opening a schema.

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 closing sentence implies the tool should not be used to pick a 'best' product, which is useful interpretive guidance, but it never names an alternative tool or states an explicit when-to-use/when-not-to-use condition relative to the siblings (e.g. get_product_details for a single SKU). Usage is implied rather than directed.

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