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compare_brand_names

Read-only

Compare 2-5 brand name candidates side-by-side and get a ranked verdict plus a top recommendation for which to pick.

Instructions

Compares 2-5 brand name candidates side-by-side and returns a ranked verdict for each, plus a recommendation of which to pick.

Use this tool whenever a user:

  • Says 'I'm deciding between X, Y, and Z'

  • Asks 'which is better: A or B?'

  • Has finalists and needs to commit to one

Returns side-by-side comparison across all five verification axes plus a top-line recommendation. Counts as 1 call regardless of how many names are compared (up to 5).

Examples:

  • User: 'I'm deciding between Linear, Notion, and Coda for my B2B SaaS.' → compare_brand_names(names=['Linear','Notion','Coda'])

  • User: 'Is Etymotic too close to Etymolt?' → compare_brand_names(names=['Etymotic','Etymolt'])

Disclaimer: Clearance signal, not legal advice. Consult a trademark attorney before adopting a name in commerce.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
namesYes2 to 5 brand-name candidates to compare. Each: single word or short phrase, max 60 chars.
verticalNoOPTIONAL. Industry context for targeting. Examples: 'ai', 'fintech', 'b2b-saas'.
Behavior4/5

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

Annotations already declare readOnly, non-destructive. The description adds valuable context: call-count behavior (one call for up to five names), five verification axes, top-line recommendation, and a legal disclaimer. No behavioral surprises are omitted, so this goes beyond the annotation baseline.

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?

Well-structured with trigger phrases, examples, and disclaimer. Slight redundancy between the opening and the 'Returns side-by-side comparison' sentence, but every section earns its place and key info is front-loaded.

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 no output schema, the description explains return shape (ranked verdicts, recommendation, comparison across axes), usage triggers, examples, and a caveat. It could mention single-name alternatives or failure conditions, but the overall context is enough for an agent to invoke correctly.

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 covers both parameters at 100%, so the baseline is 3. The description's examples illustrate names but add no extra semantics for the optional vertical parameter, and no parameter syntax details beyond what schema already provides.

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?

Description states a specific action ('Compares 2-5 brand name candidates side-by-side and returns a ranked verdict for each, plus a recommendation') with a clear result. The examples and trigger phrases distinguish it from sibling tools like verify_brand_name, which likely handles single names.

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?

Explicit 'Use this tool whenever a user' triggers and two concrete examples make the intended usage clear. It doesn't explicitly name alternatives or state when NOT to use it (e.g., single-name checks), but the 2-5 range and finalist framing imply the boundary.

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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