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Crawlora MCP

Crawlora MCP

Official
by Crawlora-org
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Remote

salon_author

Fetch a Salon writer's profile from a canonical URL, returning name, job title, bio, image, social links, and article titles with URLs.

Instructions

Get a Salon writer profile. Returns a Salon writer's profile by canonical url (https://www.salon.com/writer/<slug>): name, job_title, bio, image_url, same_as links and a list of articles. Each article carries only a title and URL, with no date or category. Job title, photo and same_as appear only when the writer page shows them.

Input Schema

NameRequiredDescriptionDefault
urlYesCanonical Salon writer URL

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.17.5

TDQS

A4.2/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses useful behavioral traits: articles carry only title and URL (no date/category), and job_title, photo and same_as appear only conditionally. This is meaningful operational context beyond a bare 'getter' statement, though it says nothing about pagination or rate limits.

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?

Front-loads the core action, then details the return fields and their conditionality in two tight sentences. Efficient overall, though the field enumeration is slightly list-heavy for the value it adds.

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

Completeness5/5

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

For a simple single-parameter, non-destructive getter with no output schema and no annotations, the description fully covers what the agent needs: input format, returned fields, and the conditional/limited nature of some data. Nothing critical is missing.

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?

With 100% schema coverage the baseline is 3, but the description adds concrete value by spelling out the exact canonical URL format (https://www.salon.com/writer/<slug>), clarifying what 'canonical' means beyond the schema's terse 'Canonical Salon writer URL'.

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 Salon writer profile') and immediately distinguishes itself from siblings like salon_article and salon_news by scoping to a writer. The agent knows exactly what entity it retrieves without opening a 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?

Implicitly signals usage by giving the canonical URL pattern (https://www.salon.com/writer/<slug>), which tells the agent what input form is expected. However, it never states when to prefer this tool over alternatives (e.g. salon_article for article lookup), leaving selection to inference.

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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