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yessGlory17

JobVerify

check_typosquatting

Read-onlyIdempotent

Detect lookalike domains that impersonate a brand by analyzing typos, homographs, and suspicious TLDs. Input a domain and optional brand to check for typosquatting.

Instructions

Detect lookalike / typosquatting / homograph domains (offline, no key): brand embedded with extra words ('google-careers'), near-miss typos ('linkedln'), IDN/punycode confusables, and high-abuse TLDs ('.top').

Use when: you have a domain and a real brand it might be impersonating.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Annotations already provide readOnlyHint and idempotentHint. Description adds key behavioral traits: 'offline, no key', and lists detection types (IDN, typos, high-abuse TLDs). No contradiction.

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 concise sentences, front-loaded with core purpose. Every sentence adds value without redundancy.

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?

Tool is simple with one required param and optional brand/format. Description covers core detect function, usage context, and operational constraint. Output schema exists to handle return details.

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?

Input schema has descriptions for all parameters (100% coverage). Description adds marginal value by explaining brand usage with examples, but not significantly beyond schema.

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?

Clear verb 'detect' with specific resource 'lookalike/typosquatting/homograph domains'. Provides concrete examples like 'google-careers' and 'linkedln'. Distinguishes from sibling 'find_lookalike_domains' by focusing on brand comparison.

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?

Explicitly states when to use: 'you have a domain and a real brand it might be impersonating'. No explicit when-not or alternatives, but context is clear and relevant.

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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