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Crawlora MCP

Crawlora MCP

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gq_author

Retrieve a GQ contributor profile by slug or canonical URL, including name, title, bio, headshot, social links, and paginated recent articles.

Instructions

Get a GQ contributor profile. Returns a GQ contributor profile, identified by slug (such as tom-ward) or by a canonical url; provide exactly one. The response has the name, job title, biography, headshot, social links and one page of recent articles. page runs from 1 to 100 (default 1) and has_next_page signals more. Unknown contributors return 404.

Input Schema

NameRequiredDescriptionDefault
urlNoCanonical www.gq.com/contributor/<slug> URL; alternative to slug
pageNo1-based page of the contributor's article list (1-100)
slugNoContributor slug, e.g. tom-ward; provide slug or url

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.17.5

TDQS

A3.9/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does reasonably well: it discloses the pagination model (page 1-100, has_next_page signals more) and the error behavior (unknown contributors return 404). It omits auth requirements and rate limits, but the disclosure of pagination and failure semantics is substantive context beyond a bare read-only profile fetch.

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

Conciseness4/5

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

Three front-loaded sentences that each carry information; the identifier options come first, then output shape, then pagination. Slight redundancy in the opening ('Get a GQ contributor profile. Returns a GQ contributor profile...') restates the same fact, costing a point.

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?

With no output schema and no annotations, the description must explain returns and behavior, and it does both: it enumerates the response fields and the pagination/404 semantics. It is complete enough to call the tool correctly, with only auth and edge-case rate-limit behavior left unstated.

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?

Schema description coverage is 100%, so the schema already documents slug, url and page. The description adds only the default value for page ('default 1') and the exactly-one-of constraint, which the schema largely conveys already ('alternative to slug'). Baseline 3 is appropriate given the schema does the heavy lifting.

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?

States a specific verb and resource (get a GQ contributor profile) and immediately describes the unique output shape – biography, headshot, social links, recent articles – which separates it from siblings like gq_article and gq_news. An agent can identify it as the contributor-entity tool without opening the schema.

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

Usage Guidelines3/5

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

The description adds a real constraint – 'provide exactly one' of slug or url – which is useful identifier guidance. However it never states when to prefer this tool over gq_article or gq_headlines, nor any prerequisite or alternative routing. Usage is implied rather than explicit.

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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