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bordeaux.guru — Bordeaux en primeur & terroir

get_phenology

Vine phenology windows (budbreak, flowering, veraison, harvest) for a Bordeaux vintage, as reported in official château brochures ('údaje château'). Sparse, documented vintages only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
vintageNoVintage year, e.g. 2025. Omit for the latest documented vintage.
appellationNoOptional appellation filter (name or slug)

TDQS

A3.8/5.0
Behavior4/5

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

With no annotations provided, the description carries the full behavioral disclosure burden. It warns that data is sparse and available only for documented vintages, and it indicates that the source is official château brochures, setting expectations about coverage and provenance without revealing internal state.

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 two sentences, front-loads the core resource and data phases, and caps usage expectations with the sparse-data caveat. No sentence is wasted; everything included supports invocation decisions.

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?

For a simple optional-parameter getter with no output schema, the description conveys the fundamental return intent (phenology windows) and important coverage limitations. It lacks explicit output formatting details, but the schema plus this description give an agent enough to reason about the call.

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?

The input schema already covers both parameters completely with descriptions, so no additional semantic burden falls on the tool description. The phrase 'for a Bordeaux vintage' hints at the vintage parameter but adds no detail beyond the schema's own documentation.

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

Purpose4/5

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

The description clearly identifies the resource as vine phenology windows (budbreak, flowering, veraison, harvest) for a Bordeaux vintage. It effectively distinguishes itself from broader tools like get_vintage_profile or get_climate_season by anchoring the data source and scope, though it does not name a sibling explicitly.

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

Usage Guidelines3/5

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

The 'Sparse, documented vintages only' caveat implies when the tool will be useful, but there is no explicit guidance on when to choose this over get_vintage_profile or get_climate_season. The optional appellation and vintage parameters give some context, but no alternatives are named.

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