Look up named vineyard sites (lieux-dits) in Bordeaux appellations — cadastral open data mapped by bordeaux.guru (e.g. BAGES or BATAILLEY in Pauillac). Search by name and/or appellation.
| Name | Required | Description | Default |
|---|---|---|---|
| name | No | Site name or its part, e.g. 'bages'. Omit to list sites of an appellation. | |
| appellation | No | Appellation name or slug to limit the search |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden of behavioral disclosure. It adds useful context about the origin of the data and gives concrete examples, but it does not describe behavior such as whether matching is fuzzy, case-insensitive, or limited, nor does it mention what the output looks like. For a read-only lookup these gaps are minor but still worth noting.
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 two sentences long with every clause earning its place: purpose, scope, data source, examples, and search dimensions. It is front-loaded with the main action and resource, making it easy to parse.
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 read-only lookup with two optional parameters, the description plus schema covers the common use cases well. It does not explicitly describe the return shape or list fields, which would be more valuable given no output schema is present, but the verb 'Look up' and the known resource type make the output fairly predictable.
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?
The input schema has 100% description coverage for its two parameters, so the schema already explains 'name' and 'appellation' with defaults and clear semantic hints. The description adds only a high-level summary ('Search by name and/or appellation'), which does not go beyond the structured field descriptions.
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 states a specific verb ('Look up'), a resource type ('named vineyard sites / lieux-dits'), a geographic scope ('in Bordeaux appellations'), and the data source ('cadastral open data mapped by bordeaux.guru'). This makes it easy to distinguish from sibling tools like get_terroir, get_parcel_varieties, or search_wines without needing to inspect schemas.
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 provides clear context on how to use the tool: 'Search by name and/or appellation.' It implies that omitting one of the parameters is valid, and the schema further clarifies the omit-to-list behavior. It does not explicitly name alternative tools or say when not to use it, but the lookup scope is distinct enough from its siblings.
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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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.