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amati032-dev

CrawlBit MCP

by amati032-dev

Brand entity check

crawlbit_entity_check

Evaluate on-site signals to check if AI can distinguish a brand as a clear entity: schema, name, description, logo, and sameAs profiles. Use when AI confuses or vaguely describes a brand.

Instructions

Checks whether a brand reads as a clear, consistent entity that AI can recognise: Organization schema, a consistent name, a description, a logo and linked profiles (sameAs). AI engines struggle to name a brand they cannot identify as a distinct thing. Use this when a brand is confused with another, or described vaguely, in AI answers. Measures the signals published on the site itself, not the brand's reputation across the web.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesThe site to analyse, e.g. example.com or https://example.com
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses that the tool measures on-site signals only and not web-wide reputation, which is a key behavioral trait. It could add more about return format or side effects, but for a read-only check this is sufficient.

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?

The description is concise, front-loaded with the purpose, and every sentence serves a purpose: purpose, context, usage, scope. No fluff or redundant repetition.

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?

Given the simplicity (one parameter, no output schema, no annotations), the description adequately covers what the tool does, when to use it, and its limitations. The only gap is not describing the output format, but that is not required for a straightforward check tool.

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 coverage is 100% for the single url parameter, with a clear description in the schema. The tool description adds minimal semantics beyond implying the URL is the site to analyse. Baseline 3 is appropriate.

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 the tool checks whether a brand reads as a clear, consistent AI-recognizable entity, listing specific signals (Organization schema, name, description, logo, sameAs). This is a specific verb+resource that clearly distinguishes it from sibling tools like offpage gaps or shopping.

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

Usage Guidelines5/5

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

Explicit usage guidance is given: 'Use this when a brand is confused with another, or described vaguely, in AI answers.' It also excludes external reputation ('not the brand's reputation across the web'), clarifying its scope versus other possible tools.

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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