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fastcompany_article

Fetch Fast Company article metadata and body paragraphs from a canonical URL. Uses a production browser fleet to complete bot-verification challenges and return clean content.

Instructions

Get Fast Company article content. Returns public Fast Company article metadata and body paragraphs from a canonical article URL. The service uses the configured production browser fleet when ordinary HTTP transport encounters Fast Company's bot-verification challenge; it does not bypass authentication or access controls.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesCanonical Fast Company article URL

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.17.5

TDQS

A4.4/5.0
Behavior5/5

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

No annotations are provided, so the description carries the full behavioral burden. It discloses that only public content is returned, that a production browser fleet may be used when bot verification blocks ordinary HTTP, and that it does not bypass authentication or access controls – valuable caveats for an agent deciding whether to call it.

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?

Three tight sentences with the purpose front-loaded, return information second, and behavioral caveats last. There is no redundant or filler content.

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 one-parameter read tool with no output schema, the description covers input, return value type, and important transport/auth caveats. It could be more explicit about exact metadata fields or failure behavior, but nothing necessary for a correct call is missing.

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

Parameters3/5

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

The single url parameter is fully documented in the schema as 'Canonical Fast Company article URL', and the description repeats this without adding examples, format rules, or constraints. With 100% schema coverage, the baseline of 3 applies.

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 clearly identifies the action ('Get'), the resource ('Fast Company article'), and the output ('metadata and body paragraphs'). The mention of 'canonical article URL' differentiates it from sibling tools like fastcompany_headlines, fastcompany_news, and fastcompany_sections.

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 gives clear invocation context: pass a canonical Fast Company article URL to obtain article content. It does not explicitly name alternatives or exclusion conditions, but the input/output framing makes the use case obvious enough for an agent.

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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