List the controlled vocabulary for a dimension — categories, use cases, platforms, audiences or pricing models. Call this to discover the exact filter values appboard_find_products accepts, and to answer "what categories exist". Each term carries the appboardUrl of its browse page.
| Name | Required | Description | Default |
|---|---|---|---|
| kind | Yes | which vocabulary to list: category, use_case, platform, audience or pricing |
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?
With no annotations provided, the description carries the full burden of explaining behavior. It discloses that the tool lists vocabulary terms and that each term includes the appboardUrl of its browse page, which is useful return-shape information beyond a bare 'list' statement. It does not mention pagination or error behavior, but those are minor for such a simple read-only tool.
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?
Three sentences with no fluff: it names the resource, states when to use it, and reveals the key return characteristic. The structure front-loads the core purpose before the usage note.
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 one-parameter, low-complexity tool, the description covers what it does, why to use it, and a key detail of its output. It is slightly shy of fully complete because it does not describe the full term structure beyond appboardUrl, but the schema and simplicity compensate.
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 coverage is 100% and the schema already describes the kind parameter and its allowed values. The description repeats those values but adds no new parameter-level detail beyond connecting them to appboard_find_products filters, so the baseline of 3 is appropriate.
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 ('List') and resource ('controlled vocabulary for a dimension'), and enumerates the supported vocabularies. It also distinguishes the tool from product-search siblings by framing it as the way to discover the exact filter values appboard_find_products accepts.
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 explicitly tells the agent when to call this tool: to discover filter values for appboard_find_products and answer questions like 'what categories exist'. It does not exhaustively list when-not-to-use cases against all siblings, but the context is clear enough for correct selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.