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

Annotations already declare readOnly, idempotent, non-destructive, and closed-world, so safety is covered. The description adds genuine behavioral context beyond that: the response is aggregated counts grouped by suit and kind, and the tool is intended as a discovery/orientation step. Return format specifics are unnecessary since an output schema exists.

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 short sentences: the first defines the output, the second defines the use case. Front-loaded, zero filler, and the example is compact and illustrative.

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 parameters, a present output schema, and full annotation coverage, the description only needs to convey intent — which it does by explaining both the grouping dimension and the pre-search orientation role. Minor gap: it never clarifies the 'suit'/'kind' vocabulary for an agent unfamiliar with the domain.

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?

The tool takes zero parameters, so there is nothing for the description to disambiguate; baseline 4 applies. The description correctly implies a parameterless, whole-corpus scan rather than a filtered query.

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 concrete deliverable — 'card counts per suit and per kind' — with a parenthetical example (camera: shot, move, lens, light) that makes the aggregation semantics unambiguous. It is clearly an inventory/aggregation tool rather than a search tool, though it does not name any sibling to sharpen the contrast.

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?

It gives an explicit usage moment: 'Use it to see what the lookbook covers before searching,' which frames this as an orientation step preceding search-style siblings like find_styles. It stops short of naming the alternatives or stating when-not to use it, so it is clear context rather than full routing guidance.

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