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

Annotations already declare readOnly, idempotent, non-destructive, and closed-world, so the safety profile is covered. The description adds real behavioral context beyond that: which dishes receive richer 'full page' results and the explicit guarantee that any other dish is still answered, which tells the agent not to fear unmatched input.

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 core capability is front-loaded in the first sentence and the fallback guarantee is second. The 22-item dish enumeration is long but earns its place by signaling result depth for those inputs; it is the only arguable bloat.

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 single-parameter, read-only lookup with an output schema and rich annotations, the description covers purpose, expected input domain, and coverage behavior. Return-value details and bottle-vs-pairing boundaries are left to the output schema and siblings respectively, which is reasonable.

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 100% and the single 'dish' parameter already carries examples ('steak', 'pizza', 'thai food'), so the description's dish enumeration adds little semantic precision beyond the schema. Baseline 3 applies since the schema does the heavy lifting.

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 task: recommend wine for a dish, complete with grape varieties and purchasable bottles. It is immediately distinguishable from the sibling tools (search_bottles, price_index, ships_to), though it gestures at 'real bottles to buy' without explicitly distinguishing itself from recommend_bottles or bottle_offers.

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 description implies when the tool applies (any dish, with a 'full page' for listed staples) and guarantees a graceful answer for unlisted dishes, but it names no alternatives and gives no when-not-to-use guidance. An agent must infer that this is the pairing-intent tool versus the bottle-search siblings.

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