list_ranges
Liste les 8 gammes de vins Maison CHAPE avec leur description et leur URL.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Liste les 8 gammes de vins Maison CHAPE avec leur description et leur URL.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full disclosure burden. It does state what is returned (the 8 ranges with their description and URL), which is nearly complete behavioral disclosure for a zero-parameter list operation. It does not explicitly confirm the operation is read-only and side-effect-free, but nothing in the description suggests otherwise.
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?
A single sentence that front-loads the action and contains zero filler. Every element — the count (8), the resource, and the output fields — earns its place.
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?
Given the trivial complexity (no parameters, no output schema, no annotations), the description covers everything an agent needs: what the tool does and what it returns. The stated return content (descriptions and URLs) adequately substitutes for a missing output schema.
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 tool has zero parameters and the input schema is empty, so the baseline of 4 applies. There are no parameter semantics for the description to clarify.
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 uses a specific verb ('Liste') with a precise resource ('les 8 gammes de vins Maison CHAPE') and specifies the output content (description et URL). The scope is explicit — exactly 8 ranges, unfiltered — and the tool is clearly distinct from siblings like food_pairing, get_brand, and where_to_buy.
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 usage context is implied: an agent would select this tool when it needs the catalog of CHAPE wine ranges. However, there is no explicit when-to-use/when-not-to-use guidance and no mention of the sibling alternatives, so the agent must infer the selection logic from the name and purpose alone.
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.
Each tool has a clearly distinct purpose: food pairing, brand facts, range listings, and purchase locations. There is no meaningful overlap or ambiguity between them.
Two tools follow a clear verb_noun pattern (get_brand, list_ranges), but food_pairing and where_to_buy break that pattern. The names are still readable and understandable, but the conventions are mixed.
Four tools is well-scoped for a brand-focused server covering identity, products, pairings, and availability. Each tool serves a distinct consumer need without bloat.
The server covers the core brand information journey: learn about the house, explore ranges, get pairing advice, and find purchase options. A minor gap is the lack of a tool for retrieving detailed individual cuvée information, but this is workable through the range URLs.