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

Annotations already cover read-only and idempotent semantics, and the description adds real behavioral context on top: input constraints (1-8 plain words, no SQL/special characters), currency and scale for the numeric filters, and the error contract that invalid enum values return a message listing allowed values. It does not disclose result-set size, pagination, or what a data-maturity tier actually signifies.

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?

Front-loads the purpose in one sentence, then walks parameters in a compact ordered list with no filler. The telegraphic fragments are efficient, though the unexplained "data-maturity tier" phrase leaves a loose end.

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 six parameters, no output schema, and zero schema coverage, the description steps up by documenting each parameter and the error path, which is enough to call it correctly. It falls short on return-side expectations, since nothing says how many results come back or what fields/tier values to expect, and there is no output schema to cover that gap.

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 0%, so the description carries the full burden and does so: it constrains query length and character set, explains category_id as a top-level slug sourced from list_categories, enumerates all four sort values with the default behavior, states that price filters are USD floats, and pins min_rating to a 0-5 scale. Every one of the six parameters gains meaning that the schema alone does not provide.

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 and resource ("Search for candidate products matching a query") and adds the distinguishing notion that results are candidates carrying a data-maturity tier, which separates it from exact-lookup siblings like get_product. It does not explicitly name those siblings, so the differentiation is implied rather than spelled out.

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?

Offers implied routing guidance via the category_id reference to list_categories and the note to omit sort for relevance order, but never says when to prefer this over compare_products, get_top100, or get_product, and lists no exclusions or prerequisites.

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