List accepted The Sun sections, such as news, sport, and tech, with slug, name, and URL to identify valid categories for headline queries.
Get The Sun sections. Lists the The Sun sections that the headlines endpoint accepts, such as news, politics, royal-family, sport, showbiz, money, tech, fabulous, travel and health. Each entry has a slug, a display name and a section 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 exist, so the description carries full burden, and it does disclose the shape of each returned entry (slug, display name, url) plus the fact that the set is the accepted vocabulary of another endpoint. It still doesn't state that this is a read-only, side-effect-free lookup or whether the list is exhaustive/stable.
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, front-loaded with the purpose, then concrete example slugs, then the entry shape. The example list is long but serves selection (an agent sees real slugs), so it earns its place; minor padding in the repeated 'The Sun sections' phrasing.
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 zero-parameter listing tool with no annotations and no output schema, the description covers purpose, example values, and returned fields, which is most of what an agent needs. It stops short of saying whether the list is complete or how it relates to the individual sun_<section> style siblings.
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 takes zero parameters, so the baseline of 4 applies. The description correctly omits parameter discussion and instead spends its space on output fields, which is the right place given the empty input schema.
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 The Sun sections. Lists the The Sun sections...') and pins down the exact scope: valid section values for the headlines endpoint. An agent can distinguish it from sun_headlines, sun_news, or sun_article without opening 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?
Usage is implied rather than stated: by naming the sections as the values 'the headlines endpoint accepts,' it signals this is a discovery/validation call before hitting headlines. It never explicitly says when to call it, when not to, or names a sibling tool as the alternative.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.