Search your drink inventory for bottles by brand, category, or beverage name using accent- and case-insensitive substring filters.
List bottles using optional accent/case-insensitive substring filters.
| Name | Required | Description | Default |
|---|---|---|---|
| brand | No | ||
| category | No | ||
| beverage_name | No |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description bears the burden of behavioral disclosure. It adds useful matching semantics (accent-insensitive, case-insensitive, substring), but does not mention return shape, pagination, or explicitly confirm read-only behavior.
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 entire description is one tight, front-loaded sentence with no filler. Every word contributes either the action or the filter behavior.
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 list with three optional, self-explanatory parameters, the description gives the core invocation details and filter semantics. Missing return-shape details are a minor gap, but the lack of output schema and annotations makes the description merely adequate rather than complete.
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 description coverage is 0%, so the description must compensate. It conveys that all filters are optional and use substring matching with accent/case-insensitivity, giving meaning beyond the raw param names. However, it does not explain how multiple filters combine or define each parameter's exact scope.
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 and resource: 'List bottles' with optional filters, which clearly identifies the operation. It is distinct from siblings like add_bottle or get_inventory_summary, though it does not explicitly name an alternative.
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?
There is no guidance on when to choose this tool over siblings such as get_inventory_summary or recommend_cocktails_from_inventory, and no conditions or excluded cases are given. The description only states what the tool does, not when to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.