MCP HubMCP Hub
Volver a habilidades

naming-6-gates

guia-matthieu
Actualizado 2 days ago
4 vistas
111
20
111
Ver en GitHub
Metaai

Acerca de

Esta habilidad genera nombres de marca o producto optimizados para 2026, asegurando que funcionen en todos los idiomas, asistentes de voz y sistemas de IA, evitando conflictos de marca registrada. Sigue un protocolo estructurado que prioriza la compatibilidad con máquinas y la defensibilidad legal. Úsela cuando los enfoques de nomenclatura estándar fallen o cuando necesite un nombre diseñado para motores de descubrimiento modernos.

Instalación rápida

Claude Code

Recomendado
Principal
npx skills add guia-matthieu/clawfu-skills -a claude-code
Comando PluginAlternativo
/plugin add https://github.com/guia-matthieu/clawfu-skills
Git CloneAlternativo
git clone https://github.com/guia-matthieu/clawfu-skills.git ~/.claude/skills/naming-6-gates

Copia y pega este comando en Claude Code para instalar esta habilidad

Documentación

Naming 6-Gates Protocol

Overview

Brand naming in 2026 is architectural engineering, not creative brainstorming. A name must be:

  1. Machine-compatible - tokenized efficiently by LLMs, citeable by AI engines
  2. Legally defensible - clear of trademark conflicts across jurisdictions
  3. Voice-ready - pronounceable by assistants, invocable without friction
  4. Narratively loaded - capable of carrying a brand story

Core principle: Optimize for AEO (Answer Engine Optimization) first, aesthetics second.

When to Use

  • Creating a new brand, product, or company name
  • Replacing a name due to trademark conflict
  • Expanding internationally (multilingual requirements)
  • Launching a voice-activated product or skill
  • Naming for AI-first discovery (ChatGPT, Perplexity, Gemini recommendations)

When NOT to Use

  • Internal project codenames (no legal/AEO requirements)
  • Temporary campaign names
  • Personal projects with no commercial intent

The 6-Gate Naming Process

digraph naming_process {
    rankdir=TB;
    node [shape=box];

    brief [label="1. BRIEF\nDefine constraints"];
    generate [label="2. GENERATE\nAI-assisted creation"];
    filter [label="3. LINGUISTIC FILTER\nMultilingual stress test"];
    legal [label="4. LEGAL FILTER\nTrademark screening"];
    aeo [label="5. AEO FILTER\nEntity strength test"];
    story [label="6. STORY FILTER\nNarrative potential"];

    brief -> generate -> filter -> legal -> aeo -> story;

    filter -> generate [label="fails" style=dashed];
    legal -> generate [label="conflicts" style=dashed];
    aeo -> generate [label="weak entity" style=dashed];
    story -> generate [label="no narrative" style=dashed];
}

Gate 1: BRIEF (Constraints Definition)

Define hard constraints BEFORE generating:

ConstraintTargetWhy
Length7-8 letters maxMobile icons, cognitive load, tokenization
Syllables1-3 syllablesVoice invocation, memorability
Character setA-Z onlyDomain availability, global keyboards
Forbidden sequencesght, ough, silent lettersPronunciation barriers

Output format:

brief:
  max_letters: 8
  max_syllables: 3
  target_markets: [FR, ES, US, UK]
  nice_classes: [9, 35, 42]
  avoid_phonemes: [ʒ, θ, ð]  # Hard for non-native speakers
  competitor_names: [Notion, Figma, Linear]  # Style reference
  forbidden_associations: [medical, financial, religious]

Gate 2: GENERATE (AI-Assisted Creation)

Use structured prompting with 5 typologies:

Typology 1: Analogical (Real-Word Transfer)

Words from unrelated domains applied to new context.

  • Examples: Apple (tech), Amazon (retail), Jaguar (auto)
  • Prompt: "Find words from [nature/mythology/geography] that evoke [core attribute]"

Typology 2: Metaphorical (Abstract Concept)

Abstract concepts made concrete.

  • Examples: Slack (workspace tension release), Notion (idea capture)
  • Prompt: "What single word captures the transformation from [pain] to [outcome]?"

Typology 3: Neologism (Invented Word)

New words with phonetic engineering.

  • Examples: Kodak, Xerox, Häagen-Dazs
  • Prompt: "Create a 2-syllable word with [plosive start] + [open vowel] + [soft ending]"

Typology 4: Portmanteau (Fusion)

Blend of two meaningful words.

  • Examples: Instagram (instant + telegram), Pinterest (pin + interest)
  • Prompt: "Blend [word1] + [word2] keeping recognition of both roots"

Typology 5: Empty Vessel

Meaningless but phonetically pleasing.

  • Examples: Rolex, Vimeo, Skype
  • Prompt: "Generate 5-letter combinations: CVCVC pattern, no existing meaning"

Generation Contract:

CONSTRAINTS:
- Max 8 letters
- Pronounceable in French, Spanish, English
- No existing trademark in Class 42
- Distinct from: [competitor list]

OUTPUT FORMAT per candidate:
- Name: [word]
- Typology: [1-5]
- Phonetic: /IPA transcription/
- Syllables: [count]
- Rationale: [1 sentence]

Gate 3: LINGUISTIC FILTER (Multilingual Stress Test)

Test each candidate across target markets:

Pronunciation Test

Run through TTS engines in 15+ languages:

  • Google TTS, Amazon Polly, Azure Speech
  • Listen for: mispronunciation, confusion, awkwardness

Cultural Connotation Check

Verify no negative meanings in:

  • Target market slang (TikTok, Douyin, RedNote trends)
  • Historical associations
  • Religious/political sensitivities
  • Homophones in local languages

Phonetic Hazards to Avoid

HazardExampleImpact
Silent letters"Knight"Voice assistant failure
Consonant clusters"Strengths"Non-native difficulty
Ambiguous vowels"Read" (reed/red)Confusion
Cross-language homophones"Gift" (poison in German)Negative association

Kill criterion: If TTS mispronounces in >2 target markets, reject.


Gate 4: LEGAL FILTER (Trademark Screening)

Phase 1: Quick Disqualification

  • Google: "[name] company" / "[name] brand" / "[name] trademark"
  • Domain check: .com, .co, .io, .fr, .eu
  • Social handles: Namechk scan all platforms

Phase 2: Formal Trademark Search

RegistryToolCheck For
FranceINPI data.inpi.frExact + phonetic similarity
EUEUIPO eSearch / TMviewSame Nice classes
USUSPTO TESSRegistered + pending
InternationalWIPO Global Brand DatabaseMadrid Protocol

Phase 3: AI-Assisted Similarity Detection

EUIPO "Early TM Screening" detects:

  • Phonetic similarity (sounds-like)
  • Visual similarity (looks-like)
  • Conceptual similarity (means-like)

Kill criterion: Any conflict in target Nice classes → reject.


Gate 5: AEO FILTER (Entity Strength Test)

A name must be recognizable as a distinct entity by AI systems.

Entity Strength Checklist

  • Unique token: Does the name tokenize as a single unit or get split?
  • No collision: Search "[name]" - does it return your intended context or noise?
  • Semantic boundaries: Can AI distinguish "[name] the company" from generic usage?

Testing AEO Strength

Prompt to test:
"What is [NAME]?"

GOOD response: "I don't have information about [NAME]" (clean slate)
BAD response: "[NAME] is a common word meaning..." (collision)
BAD response: "[NAME] could refer to several things..." (ambiguity)

Keyword Difficulty Check

Use Semrush/Ahrefs:

  • Keyword difficulty < 30 = good
  • Keyword difficulty > 60 = buried by generics

Kill criterion: If name collides with high-volume generic term, reject.


Gate 6: STORY FILTER (Narrative Potential)

A name must be "tell-able" - capable of carrying a brand story.

The 5 Narrative Pillars Test

For each candidate, verify you can build:

PillarQuestionExample Answer Required
Origin story"Why this name?"Must have a genuine, shareable reason
Belief storyWhat does the brand stand for?Values must connect to name
Product truthWhat does it actually do?Name should hint at function
TransformationWhat changes for the customer?Before/after must be nameable
CultureWhat kind of community forms?Name should enable identity

Empty Vessel vs. Loaded Name

  • Empty vessel (Kodak, Google): Brand fills meaning over time
  • Loaded name (Instagram, Airbnb): Meaning is built-in

Both work. But you must choose consciously and build accordingly.

Vocal Signature Test

Say the name aloud 10 times. Ask:

  • Does it feel good in the mouth?
  • Would customers enjoy saying it?
  • Does it have a "sticky" quality?

Kill criterion: If you can't tell a compelling origin story, reject.


Voice Assistant Constraints (2026)

AssistantInvocation RulesRejection Risks
Alexa2+ words required (unless trademarked)Single generic words
SiriMust be phonetically distinctConfusion with system commands
GoogleStrong Knowledge Graph presence neededNames too similar to famous brands
BixbyAvoid wake-word conflicts"Open", "cancel", common verbs

Test procedure:

  1. Say "[Name], do [action]" to each assistant
  2. Note recognition rate
  3. Reject if < 80% accurate invocation

Output: Naming Dossier

For the final candidate, produce:

## [NAME] - Naming Dossier

### Basic Info
- **Name:** [word]
- **Typology:** [1-5]
- **Phonetic:** /IPA/
- **Length:** X letters, Y syllables

### Linguistic Clearance
- FR pronunciation: [pass/fail + notes]
- ES pronunciation: [pass/fail + notes]
- EN pronunciation: [pass/fail + notes]
- Cultural flags: [none / list]

### Legal Clearance
- INPI (FR): [clear / conflict]
- EUIPO (EU): [clear / conflict]
- USPTO (US): [clear / conflict]
- Domains available: [list]
- Social handles: [list]

### AEO Score
- Entity uniqueness: [1-10]
- Keyword difficulty: [score]
- Tokenization: [single/split]

### Narrative Potential
- Origin story hook: [1 sentence]
- Brand values connection: [1 sentence]
- Community identity: [suggested demonym]

### Voice Readiness
- Alexa: [pass/fail]
- Siri: [pass/fail]
- Google: [pass/fail]

### Recommendation
[APPROVED / NEEDS WORK / REJECTED]
[Final reasoning]

Common Mistakes

MistakeWhy It FailsFix
Starting with brainstormingGenerates unusable namesStart with constraints (Gate 1)
Skipping TTS testVoice assistant failuresAlways test pronunciation
Ignoring Nice class overlapTrademark conflictsCheck specific classes, not just exact matches
Choosing descriptive namesWeak AEO, hard to trademarkPrefer distinctive/invented
No narrative testBrand can't tell its storyAlways verify storytelling potential

Quick Reference

The 7-8 Letter Rule: Shorter = better for mobile, voice, memory, tokenization.

Phonetic Gold Standard: CVCV pattern (consonant-vowel-consonant-vowel) works globally.

AEO Priority: If AI can't cite you as a distinct entity, you don't exist in 2026.

Empty Vessel Strategy: Meaningless names (Kodak) require more brand-building but face fewer conflicts.

Voice-First: If Alexa can't invoke it, 8.4 billion assistants can't recommend it.


What Claude Does vs What You Decide

Claude handlesYou provide
Generating candidates by typologyBrief constraints (markets, classes)
Running linguistic stress testsFinal pronunciation judgment
Checking trademark databasesLegal professional validation
Evaluating AEO/entity strengthStrategic brand direction
Producing naming dossierFinal selection and approval

Skill Boundaries

This skill excels for:

  • Brand, product, or company naming
  • Names requiring international deployment
  • Voice-assistant compatible names
  • AI-discoverable entity creation

This skill is NOT ideal for:

  • Internal codenames → No legal/AEO requirements
  • Temporary campaign names → Overhead unnecessary
  • Personal projects → Simplified process sufficient

Skill Metadata

name: naming-6-gates
category: branding
version: 2.0
author: GUIA
source_expert: 6-Gate Protocol (AEO-first naming)
difficulty: advanced
mode: centaur
tags: [naming, branding, trademark, voice-assistant, aeo, entity]
created: 2026-02-03
updated: 2026-02-03

Repositorio GitHub

guia-matthieu/clawfu-skills
Ruta: skills/branding/naming-6-gates
0
ai-skillsanthropicclaude-codeclaude-skillsmarketingmcp-server

Habilidades relacionadas

content-collections

Meta

Esta habilidad proporciona una configuración probada en producción para Content Collections, una herramienta centrada en TypeScript que transforma archivos Markdown/MDX en colecciones de datos con tipado seguro mediante validación Zod. Úsala al construir blogs, sitios de documentación o aplicaciones Vite + React con mucho contenido para garantizar seguridad de tipos y validación automática de contenido. Abarca todo, desde la configuración del plugin de Vite y compilación MDX hasta la optimización de despliegue y validación de esquemas.

Ver habilidad

polymarket

Meta

Esta habilidad permite a los desarrolladores crear aplicaciones con la plataforma de mercados de predicción Polymarket, incluyendo la integración de API para operaciones y datos de mercado. También proporciona transmisión de datos en tiempo real a través de WebSocket para monitorear operaciones en vivo y actividad del mercado. Úsela para implementar estrategias de trading o crear herramientas que procesen actualizaciones de mercado en tiempo real.

Ver habilidad

creating-opencode-plugins

Meta

Esta habilidad ayuda a los desarrolladores a crear complementos de OpenCode que se conectan a más de 25 tipos de eventos, como comandos, archivos y operaciones LSP. Proporciona la estructura del complemento, las especificaciones de la API de eventos y los patrones de implementación para módulos en JavaScript/TypeScript. Úsala cuando necesites interceptar, monitorear o extender el ciclo de vida del asistente de IA de OpenCode con lógica personalizada basada en eventos.

Ver habilidad

sglang

Meta

SGLang es un framework de alto rendimiento para el servicio de LLM que se especializa en generación rápida y estructurada para JSON, expresiones regulares y flujos de trabajo de agentes utilizando su caché de prefijos RadixAttention. Ofrece una inferencia significativamente más rápida, especialmente para tareas con prefijos repetidos, lo que lo hace ideal para salidas complejas y estructuradas, y conversaciones multiturno. Elige SGLang sobre alternativas como vLLM cuando necesites decodificación restringida o estés construyendo aplicaciones con uso extensivo de prefijos compartidos.

Ver habilidad