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fastcompany_headlines

Retrieve current headlines from any Fast Company section using its slug. Get clean JSON feed of fresh stories for topics like technology or artificial intelligence.

Instructions

Get Fast Company section headlines. Returns fresh headlines from one Fast Company section or topic's public RSS feed. section accepts any slug returned by GET /fastcompany/sections (78 values, e.g. "technology" or "artificial-intelligence").

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sectionYesFast Company section slug, from GET /fastcompany/sections

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.17.5

TDQS

A4.2/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the behavioral burden. It does add useful context: results are 'fresh' headlines pulled from a 'public RSS feed,' implying recency and no auth. However, it does not disclose count, ordering, or output shape, which a richer description could provide.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences with no filler. The core action and scope are front-loaded, and the parameter guidance is compact and immediately useful.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple one-parameter headlines tool, the description covers the essential call context: what to pass and where to find valid values. An output schema is absent, but the phrase 'returns fresh headlines' sufficiently implies a list of headlines for basic invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3. The description adds meaningful value by explaining that 'section' accepts slugs from GET /fastcompany/sections, noting there are 78 values, and giving concrete examples like 'technology' and 'artificial-intelligence'. This exceeds the schema's brief pointer.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb ('Get'), resource ('Fast Company section headlines'), and the data source ('public RSS feed'). It clearly distinguishes this from siblings like fastcompany_article or fastcompany_news by scoping to section-level headlines.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description makes the usage context clear: use it to retrieve fresh headlines for a specific Fast Company section or topic. It does not explicitly exclude alternatives or name sibling tools, but the section-focused scope is unambiguous.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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