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

Annotations already declare readOnly, openWorld, idempotent, and non-destructive behavior. Beyond that, the description adds meaningful context: it uses Qloo's taste graph to score candidates and returns the option that maximizes the least happy person's happiness, with a reason per person. That reveals the selection logic and return content, though it does not discuss failure modes or rate limits.

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?

The description is a single dense paragraph but is front-loaded with the core action and packs almost every sentence with useful information. It is appropriately sized for the tool's complexity, though the run-on structure could be easier to scan.

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?

Given four parameters, low schema coverage, no output schema, and no sibling tools, the description covers the essential inputs, the taste-transfer mechanism, the scoring objective, and the return shape (a pick plus per-person reasons). It omits minor constraints such as the maximum group size, but an agent can call it correctly from this definition.

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 only 25%, so the description must compensate, which it does: it explains the `kind` categories, the 2–5 `likes` per member, the `location` requirement for places, and the purpose of `tasteFrom` with concrete examples including `any`. It leaves some constraints like the maximum of 8 members to the schema, but adds substantial meaning over the raw schema.

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: it picks ONE movie, TV show, book, artist, podcast, restaurant, or destination for a group. It also names the underlying mechanism, Qloo's taste graph, and the optimization goal, making the tool's function unambiguous even without sibling tools.

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 clearly explains how to use the tool: provide each person's name and 2–5 likes, use `tasteFrom` when favorites come from another category, and include `location` when `kind=place`. It does not include explicit exclusions or 'when not to use' guidance, but there are no sibling alternatives and the usage context is clear.

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