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

With no annotations provided, the description carries the full burden of behavioral disclosure. It clarifies the tool ranks by 'cheapest standing price' (implying non-discounted pricing) and optionally filters by area, but it does not disclose what the output looks like (e.g., does it return venue names, prices, or a sorted list?), nor does it mention any limitations like data freshness or venue availability. The description is honest but thin on behavioral detail, which is expected for a simple ranking tool.

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 two sentences with zero filler. The core action is front-loaded ('Rank venues by the cheapest standing price'), followed by the optional scoping and two illustrative examples. Every word earns its place, and the structure guides the reader from general capability to specific use cases.

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 tool with only three simple parameters and no output schema, the description is largely complete. It specifies the ranking criterion, the optional filter, and gives usage examples. However, since there is no output schema, it would be slightly more complete to mention the return format (e.g., a ranked list of venues with prices). The absence of that detail is a minor gap but not critical for an agent to call the tool correctly.

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 input schema already provides full descriptions for all three parameters (drink, area, limit), with 100% schema description coverage. The description adds contextual examples that reinforce how parameters are used ('beer in Kadıköy'), but it does not add new semantic meaning beyond what the schema states. Per the rubric, a baseline of 3 is appropriate when 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 specific action ('Rank venues'), a specific criterion ('cheapest standing price'), and a resource ('drink category'), with optional geographic scoping. It also provides two concrete query examples that make the tool's intent unmistakable. It distinguishes itself from siblings like happy_hours_now (which focuses on time-limited deals) by explicitly noting 'standing price'.

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 gives clear example queries ('where is the cheapest beer in Kadıköy' or 'cheap cocktails in Beyoğlu') that effectively illustrate when to use the tool. It does not explicitly state when not to use it or name alternatives, but the examples plus the 'standing price' wording implicitly steer agents away from happy-hour queries. A small gap is the absence of an explicit exclusion for time-sensitive pricing, which a sibling like happy_hours_now might handle.

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