Get the en primeur tasting note for one wine and vintage from bordeaux.guru: score, summary (CZ+EN), nose/palate/finish, structure, blend, alcohol, yield, aging potential. Free tiers receive a teaser.
| Name | Required | Description | Default |
|---|---|---|---|
| wine | Yes | Wine name or slug, e.g. 'chateau-pontet-canet' or 'Pontet-Canet' | |
| vintage | No | Vintage year, e.g. 2024. Omit for the latest tasted vintage. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Since no annotations are provided, the description carries the full burden, and it does meaningful work: it identifies the source, the returned tasting-note sections, and the tier behavior ('Free tiers receive a teaser'). It does not detail error cases or authentication, but for a read-only retrieval tool this is reasonably transparent.
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 one dense, front-loaded sentence with no filler words. It states the purpose, the resource, the output scope, and the tier limitation without repetition.
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 simple two-parameter read tool with no output schema, the description is unusually complete: it names the output fields and warns about teaser limitations for free tiers. The main missing context is sibling-selection guidance, which is already penalized under usage guidelines.
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%, so the schema already documents both parameters. The description adds context by framing them as 'one wine and vintage,' but it does not meaningfully enrich the schema-provided meaning.
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 begins with a specific verb and resource: 'Get the en primeur tasting note for one wine and vintage from bordeaux.guru.' It also enumerates the returned content, which makes it clearly distinct from sibling tools like get_chateau, get_vintage_profile, or search_wines.
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 does not state when to choose this tool over alternatives or when not to use it. It implies that it is for a single wine/vintage tasting note, but it does not mention exclusions, prerequisites, or routing to siblings such as search_wines for unknown wine names.
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.