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

Goes well beyond the annotations (which only cover read-only/idempotent safety): it discloses the paid-plan requirement, the exact cost model (1 credit per 25-row page, empty page free), and the daily per-key cap of 2,000 calls on the derived family. These are precisely the operational facts an agent needs before invoking.

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?

Long but front-loaded: the kind inventory leads, then usage guidance, then cost. The parenthetical ranking details are dense but each earns its place given the five-way kind switch. Minor density cost keeps it off a 5.

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 complex 8-parameter, 5-kind discovery tool with no output schema, the description covers purpose, per-kind semantics, usage routing, and full cost/limit context. An agent can select and invoke it correctly without further information.

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 75% and the description meaningfully extends it — it explains what each kind ranks by, which sort fields apply per kind, and the distinct behaviors of category_id (narrow top_brands) versus parent_id (children of top_categories). It adds value, though the sort field mapping is left as 'see description' rather than fully itemized.

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+resource ('Ranked LISTS from Logimu's observations, 25 per page') and enumerates all five kind values with what each ranks, so the agent knows exactly what data comes back. It clearly distinguishes itself from the sibling look-up tools (brand/seller/category), which retrieve a known entity rather than rank a set.

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?

'USE WHEN the user wants to DISCOVER brands, sellers or categories rather than look one up' gives an explicit when-to-use, with concrete scenarios (sourcing leads, brands under seller pressure, biggest resellers). It then routes the agent onward with 'Then drill in with the brand / seller / category tools,' naming alternatives and the follow-up path.

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