List New York Post RSS sections with slugs, names, and URLs, helping you find valid section identifiers for headline requests.
Get New York Post RSS sections. Lists the 54 New York Post section slugs accepted by nypost-headlines, such as us-news, politics, nfl, celebrities and mental-health. Each entry has its slug, display name and url.
| 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?
No annotations are provided, so the description carries the behavioral burden, and it does disclose the enumeration nature (fixed set of 54) plus the returned fields (slug, name, url). It omits explicit read-only/side-effect phrasing, but for a pure lookup tool this is minor.
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 tightly written sentences, front-loaded with the purpose and then the relational detail. Every clause earns its place by either naming the resource, the count, the consumer tool, or the returned fields.
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?
With no output schema, the description fully compensates by specifying the returned fields (slug, name, url) and the cardinality (54), so an agent knows exactly what a call yields without further schema support.
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?
Zero parameters, so per the rubric the baseline is 4. The description adds relevance by enumerating example slugs (us-news, politics, nfl, celebrities, mental-health) that an agent would pass to the sibling tool, giving concrete format guidance.
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?
States a specific verb and resource ('Get New York Post RSS sections') and immediately clarifies that it returns the 54 section slugs consumed by `nypost-headlines`. This distinguishes it from sibling tools like nypost_headlines and nypost_news without the agent needing to open any schema.
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?
Explicitly ties the tool to its consumer: these are the slugs 'accepted by `nypost-headlines`', which tells the agent this is a lookup/discovery step that feeds headlines retrieval. It doesn't state explicit exclusions (e.g., 'do not use for article retrieval'), so it stops short of a full 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.