/naming-6-gates

name: naming-6-gates
description: Use when creating brand names, product names, or company names in 2026. Use when naming needs to work across languages, voice assistants, and AI recommendation engines. Use when previous name candidates failed trademark or had conflicts.
license: MIT
metadata:
  author: ClawFu
  version: 1.0.0
  mcp-server: "@clawfu/mcp-skills"

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:

| Constraint | Target | Why | |------------|--------|-----| | **Length** | 7-8 letters max | Mobile icons, cognitive load, tokenization | | **Syllables** | 1-3 syllables | Voice invocation, memorability | | **Character set** | A-Z only | Domain availability, global keyboards | | **Forbidden sequences** | ght, ough, silent letters | Pronunciation 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

| Hazard | Example | Impact | |--------|---------|--------| | 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

| Registry | Tool | Check For | |----------|------|-----------| | France | INPI data.inpi.fr | Exact + phonetic similarity | | EU | EUIPO eSearch / TMview | Same Nice classes | | US | USPTO TESS | Registered + pending | | International | WIPO Global Brand Database | Madrid 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 cr