En primeur release prices of one Bordeaux wine across vintages, in EUR (ex-négociant, excluding VAT). Public data — available on every tier. Does NOT include the price position against the vintage curve, which is a members' feature on the website.
| Name | Required | Description | Default |
|---|---|---|---|
| wine | Yes | Wine name or slug, e.g. 'chateau-pontet-canet' or 'Pontet-Canet' |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses data accessibility ('Public data — available on every tier'), defines the exact data scope, and explicitly flags a member-only feature that is absent. This is strong behavioral context for a simple read-only lookup.
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?
Three short sentences, front-loaded with the core purpose, followed by essential pricing details and a useful exclusion. No filler or redundancy.
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 public lookup with no output schema, the description supplies the key missing context: what is returned, the currency, the pricing basis, and access availability. It does not specify the exact return shape, but the tool is simple enough that this is a minor gap.
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 for the only parameter is 100%, with examples and field description, so the baseline applies. The description adds value by framing the wine as 'one Bordeaux wine' and explaining price semantics, but it does not need to restate the parameter itself.
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?
States a specific resource ('En primeur release prices of one Bordeaux wine across vintages'), units (EUR), and pricing stage (ex-négociant, excluding VAT). The scope 'one Bordeaux wine' also differentiates it from broader wine-data siblings like get_vintage_profile and compare_climate.
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?
Gives clear context: this is a public-data lookup available on every tier, so an agent can infer there are no auth barriers. It also states what is not included (price position against the vintage curve), preventing misuse. It does not explicitly name sibling alternatives, but the description makes the use case obvious.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools target clearly distinct entities or actions: château, tasting note, climate, parcel, price, lieudit. A few pairs overlap—compare_climate/get_climate_season and get_tasting_note/get_bottle_tasting—but the descriptions clarify the difference well.
The naming is highly consistent: nearly all retrieval tools use the get_<noun> pattern, while compare_, lookup_, search_, and about_ represent genuinely different operation types. All names are snake_case and follow a predictable verb_noun structure.
14 tools is well-scoped for a specialized Bordeaux en primeur and terroir data server. Each tool covers a distinct data product such as tastings, climate, phenology, terroir, prices, and château profiles, without significant redundancy.
The tool set covers the primary read-only workflows: searching wines, retrieving tasting notes, exploring château/terroir data, climate comparisons, phenology, and pricing. Minor gaps exist, such as no dedicated browse/list endpoints for appellations or vintages, but these can be worked around via search and known names.