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yessGlory17

JobVerify

find_lookalike_domains

Read-onlyIdempotent

Generate typo, homoglyph, and TLD variations of a real domain to find live look-alikes used for phishing or fake recruiter infrastructure.

Instructions

Generate typo/homoglyph/TLD permutations of a REAL brand domain and return the ones that actually resolve in DNS (no key). Live look-alikes are prime fake-recruiter / phishing infrastructure.

Use when: you know the real company domain and want to hunt impersonators.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, covering safety and idempotency. The description adds minimal extra behavioral context: 'no key' and 'return the ones that actually resolve in DNS'. It does not disclose rate limits or other nuances. With annotations covering the safety profile, a 3 is appropriate.

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 two sentences plus a 'Use when' line, extremely concise and front-loaded. Every sentence adds value: defines the action, output, and use case. Zero wasted words.

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 output schema exists (not shown but present) and annotations are comprehensive, the description is mostly complete. It covers the tool's purpose and primary use case. The only gap is not mentioning optional parameters (max_checks, response_format), but these are well-documented in the schema. The description adequately fits the tool's complexity.

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

Parameters2/5

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

Schema description coverage is 0%, meaning the tool description does not explain any parameters. The schema itself has good descriptions, but the description must compensate due to low coverage. It does not add any parameter-level guidance beyond the schema, so the score is below baseline.

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 uses a specific verb 'generate' and identifies the resource 'typo/homoglyph/TLD permutations of a REAL brand domain', clearly stating the output 'ones that actually resolve in DNS'. It distinguishes from sibling tools like check_domain or check_typosquatting by focusing on generating permutations rather than checking a single domain.

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 explicitly says 'Use when: you know the real company domain and want to hunt impersonators', providing clear context. However, it does not explicitly mention when not to use or compare with alternatives like check_typosquatting, which is a sibling tool.

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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