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

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety is covered. The description adds a genuine behavioral contract beyond that: it commits to grounding output strictly in stored metadata and to never fabricating differences or suitability claims. 'Read-only and public' merely restates the annotations, adding no new information.

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 short sentences, front-loaded with the core action and cardinality, with no padding. The closing 'Read-only and public' clause is mildly redundant given the annotations, which keeps it from being perfectly economical.

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 two-parameter, fully documented, annotation-backed tool this covers purpose and grounding rules well. With no output schema, it could have said something about the shape of the comparison result, but nothing an agent needs in order to call it correctly is missing.

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 both parameters are already documented, including the fact that use_case is recorded but not used to invent claims. The description adds no syntax, format, or ID-resolution detail beyond the schema, so the baseline 3 is appropriate.

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 verb ('Compare') and resource ('products') plus a hard cardinality bound (2–4), which cleanly separates it from single-product siblings like get_product_details. It also scopes the inputs to stored metadata. It does not, however, name or contrast itself with any sibling tool, so the differentiation is inferred rather than stated.

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 2–4 product constraint and the 'use stored metadata' framing imply when the tool applies (multi-product evaluation), but there is no explicit when-to-use/when-not statement and no alternative named for the single-product or discovery cases. Usage is left to inference from the sibling list.

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