bar_find_gaps

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

No annotations are provided, so the description carries the full disclosure burden, and it does a good job: it explains that it loads constrained slots, pits them against in-stock bottles, uses a penalty-vs-threshold cut-off with hard-disqualification, and returns results sorted worst-gap-first. The only unstated traits are the read-only nature and any cost/pagination behavior, which are minor for a clearly analytical 'Find' operation.

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-loaded with a one-line purpose, followed by a compact mechanics sentence and a clean Args block; nothing is repeated and the ordering (purpose, algorithm, sort order, parameters) puts the most decision-relevant information first.

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?

An output schema exists, so return values need no explanation, and the description still usefully notes the worst-gap-first ordering. It leans heavily on domain jargon (slots, penalty, hard-cap) that a naive agent may not fully grasp, but it is consistent with the rest of the tool family, so the gap is minor.

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 0% and both parameters are only titled ("Threshold", "Cocktail Ids"), yet the Args block compensates fully: it explains cocktail_ids as a restriction with None meaning every constrained slot, and gives threshold both its default and an intuitive operational reading ("roughly two-axis miss or one hard-cap brush"). This adds genuine meaning the JSON schema lacks.

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 opening line states a concrete verb and object ("Find recipe slots where the best in-stock bottle is a stretch") and even labels the concept ("the shopping list"), so the agent knows this is a gap/shopping-list computation over flavor constraints. It does not, however, explicitly disambiguate from the sibling bar_get_shopping_list, so the agent must infer the difference from wording alone.

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?

Usage is heavily implied by the domain framing ("the shopping list") and by the deterministic algorithm described, so an agent can guess it is the analytical gap-finder rather than a plain list. But there is no explicit when-to-use/when-not-to-use statement and no named alternative (e.g. bar_get_shopping_list or bar_alternatives_for_slot) to route between them.

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