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naming

Guide name selection from trait identification through research to shortlisting.

Updated Mar 26, 2026
Search Tags:#research#brand voice#etymology#decision support#brand strategy#naming
One-click install
npx skills add https://github.com/christophevg/c3 --skill naming-christophevg
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: naming
Source: https://github.com/christophevg/c3/tree/main/skills/naming
Command: npx skills add https://github.com/christophevg/c3 --skill naming-christophevg

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It eliminates guesswork when naming a project, product, agent, or entity by turning vague preferences into a research-backed shortlist tied to real traits and practical constraints.

Core Features & Use Cases

  • Trait identification: Clarifies what relationships and qualities the name must express, including cultural, linguistic, and usability constraints.
  • Provenance-first name research: Produces 10–15 candidates with deep etymological research across multiple traditions and explicit source provenance.
  • Shortlisting and decision support: Delivers a shortlist (plus near-miss tiers) with trait-cluster mapping, comparison tables, international pronounceability checks, and honest drawback analysis.

Quick Start

Ask the naming skill to help you choose a name for your new agent by providing the key traits you want it to embody and any constraints on language, length, or pronunciation.

Frequently Asked Questions about naming

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I choose a meaningful name for a product or agent?▼

Choosing a name involves clarifying the traits and qualities the name must express, generating 10–15 candidates with multi-tradition etymological research, and evaluating a shortlist against pronunciation, historical context, and AI-association risks.

What goes into a brand naming strategy for evaluating candidate names?▼

A brand naming strategy evaluates candidates by mapping trait clusters, checking international pronounceability, analyzing historical context, and assessing AI-association risks, providing an honest drawback analysis for each option.

Can I get etymology research across multiple linguistic traditions for naming?▼

Yes, naming research produces 10–15 candidates backed by multi-tradition etymological analysis, ensuring every name suggestion includes explicit source provenance and historical context.

What is the best way to shortlist names with near-miss tiers?▼

The best way to shortlist names is by mapping trait clusters to candidates and organizing them into primary selections and near-miss tiers, allowing you to compare practical constraints like pronunciation and usability side by side.

Does naming support feature naming with specific language and length constraints?▼

Yes, naming supports feature and entity naming by accepting specific constraints on language, length, and pronunciation, filtering candidates to ensure the final shortlist meets practical usability requirements.

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