Retrieve the public vertical taxonomy used by the headlines endpoint to map sections for content categorization.
Get Variety sections. Returns the public Variety vertical taxonomy used by the headlines endpoint.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v1.17.5Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the full burden of behavioral disclosure. It openly states this is a retrieval operation ('Get', 'Returns') and clarifies the data is public taxonomy. It doesn't discuss pagination, rate limits, or response shape, but for a zero-parameter read-only tool this is reasonably transparent.
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?
Two short sentences carry the purpose, the publisher, and the relationship to the headlines endpoint. No wasted words, and the most important information is front-loaded.
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 tool has no parameters, no annotations, and no output schema, the description is nearly complete. It names the return value ('public Variety vertical taxonomy') and its consumer ('headlines endpoint'). An agent knows what to call and roughly what to expect; only a more precise shape of the taxonomy (e.g., list of slugs and names) is left unspecified, which is a minor gap for a tool this simple.
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?
There are zero parameters and schema coverage is 100%, so the baseline is 4. The description doesn't need to add parameter semantics since the empty schema fully documents the call; it correctly focuses on what the tool returns instead.
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 the explicit verb 'Get' with a specific resource ('Variety sections'), and adds that it returns the public Variety vertical taxonomy used by the headlines endpoint. This clearly distinguishes it from sibling sections tools like newyorker_sections or nyt_sections by naming the publication, and even explains its relationship to variety_headlines.
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 gives clear context by stating this is the taxonomy used by the headlines endpoint, which implies an agent should call this before variety_headlines to discover section slugs. It doesn't explicitly exclude alternatives, but among the many *_sections siblings the name and mention of 'Variety' make the intended use obvious.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.