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bordeaux.guru — Bordeaux en primeur & terroir

get_bottle_tasting

Bottle tasting notes from bordeaux.guru: wines tasted from the bottle at events, as opposed to en primeur barrel samples. Returns event, date, vintage, score, drink window and Czech retail price. The written note is for Collector/Cellar members; others get the opening line.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
wineYesWine name or slug, e.g. 'Marjosse' or 'chateau-marjosse'
vintageNoOptional vintage in the bottle, e.g. 2018. Omit for all tasted vintages.

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries the full behavioral disclosure burden. It openly states that the written note is restricted to Collector/Cellar members while others receive only the opening line, and it lists the returned fields. This is meaningful beyond the schema and helps set expectations about access-controlled output.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three focused sentences with no filler. It front-loads the core distinction, then lists the return fields, then notes the access tier difference. Every sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description enumerates the return values and explains the membership limitation, which is important since there is no output schema. It is sufficient for a low-complexity two-parameter tool, though it does not discuss edge cases like missing tasting notes or a wine with no bottle tasting record. Overall, it provides enough context for correct use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the parameter descriptions already document 'wine' and 'vintage' thoroughly. The tool description adds context about output fields but does not add new semantics about how the parameters behave. A baseline 3 is appropriate because the schema handles the parameter meaning.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states a specific verb and resource: it returns bottle tasting notes from bordeaux.guru, meaning wines tasted from the bottle at events. It also distinguishes this from en primeur barrel samples, which sets it apart from sibling tools like get_tasting_note. The scope is unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives a clear usage context: use this for bottle tastings at events, as opposed to en primeur barrel samples. It doesn't explicitly name the alternative sibling or state 'use get_tasting_note instead', but the distinction is clear enough for an agent to infer the correct tool.

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

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TDQS

A3.9/5.0
Disambiguation4/5

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.

Naming Consistency5/5

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.

Tool Count5/5

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.

Completeness4/5

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.

Resources