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

With no annotations provided, the description carries the full burden of behavior disclosure. It does well by revealing membership-gated output behavior: Collector/Cellar members receive the number, expected price, and comparison count, while everyone gets the release price. This is a meaningful behavioral trait not inferable from the schema. It could go further by noting whether lookup failures return errors or fallback, but the key access limitation is clearly disclosed.

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 compact at two sentences, with the core value proposition front-loaded in the first sentence. Each sentence earns its place: one defines the metric, the other explains what different user tiers can see. Slightly awkward phrasing ('How dear...') and the vague 'the number' prevent a perfect score.

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 no output schema and no annotations, the description should more thoroughly explain return values. It conveys the main output categories but leaves terms like 'the number' and 'the expected price' underspecified, and does not state units, currency, or what happens when data is unavailable. Given the simplicity of the two parameters, the definition is adequate but not fully complete.

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%: both wine and vintage have descriptions with examples. The description adds conceptual context (en primeur release price vs. vintage price curve) but does not materially clarify parameter formats or constraints beyond the schema. Baseline 3 is appropriate because 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 clearly identifies the tool's purpose: it communicates how expensive a Bordeaux wine is relative to its score by comparing en primeur release price to the vintage's price curve. This is a specific, meaningful function that differs from generic price lookup tools like get_wine_prices. The phrase 'How dear...' is slightly indirect, but the meaning is clear and actionable.

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 usage context: if you need to evaluate price fairness relative to wine score, this is the tool. It also distinguishes member vs. non-member visibility. However, it does not explicitly state when to prefer this over get_wine_prices or other siblings, nor does it provide exclusions or decision criteria beyond the inherent purpose.

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