mcpField
C
company-name-generator

company-name-generator

github.com/breverdbidderMarketing & growth50 installs
Repository

About company-name-generator

company-name-generator is a skill for developing and screening business names. It organizes candidates into ten naming categories, scores them against weighted criteria, and checks trademark conflicts and domain availability.

Key features

  1. 01Generates names across ten categories
  2. 02Scores candidates on five criteria
  3. 03Checks USPTO trademark conflicts
  4. 04Verifies .com, .ai, and .io availability
  5. 05Ranks the top 25 candidates

Use cases

  1. 01Develop names for a new business
  2. 02Compare names for trademark risk
  3. 03Check domain availability during brand planning

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/breverdbidder/life-os --skill company-name-generator

After installing, type/company-name-generatorin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

references/
naming_best_practices.md
scripts/
check_availability.py
generate_names.py
name_generator.py

Details

From the project README

Company Name Generator

Systematic business naming with trademark screening and domain availability validation.

Core Workflow

  1. Extract business context (domain, audience, competitive positioning, IP requirements)
  2. Generate 5-15 names per category (10 categories)
  3. Score each name 0-100 across 5 weighted criteria
  4. Check USPTO TESS for trademark conflicts
  5. Verify .com/.ai/.io domain availability
  6. Present top 25 ranked names with availability data

10 Naming Categories

Descriptive - Direct function description. Clear but may lack trademark strength.
Metaphoric - Evoke imagery/emotions. Strong storytelling (e.g., "Everest", "Summit").
Invented - Unique coined words. Highest trademark strength (e.g., "Auctioniq").
Founder-Based - Personal brand authority. Clear IP ownership (e.g., "Shapira Formula").
Acronym - Memorable initialisms (e.g., "APEX").
Compound - Two-word combinations (e.g., "BidDeed", "LienLogic").
Foreign Language - Sophistication/authority (e.g., "Veritas").
Playful - Approachable, memorable (e.g., "BidWise").
Geographic - Place-based authority (e.g., "Brevard BidTech").
Legacy - Institutional authority (e.g., "The Shapira Group").

Scoring Formula (0-100)

Score = (Trademark×0.30) + (Domain_Signal×0.25) + (Tech_Signal×0.25) + (Metaphor×0.10) + (Memo×0.10)

Trademark Strength (30%): USPTO conflict risk
Domain Signal (25%): Industry/function clarity
Tech Signal (25%): AI/ML/automation implication
Metaphor Power (10%): Storytelling/pitch strength
Memorability (10%): Ease of recall/pronunciation

USPTO & Domain Checking

Use scripts/check_availability.py to verify both:

python scripts/check_availability.py "Company Name" --classes 9,42 --tlds com,ai,io

Trademark Classes:

  • Class 9: Software
  • Class 42: SaaS
  • Class 41: Education (if methodology/certification)

Risk Levels:
LOW (0-1 conflicts) | MEDIUM (2-4 conflicts) | HIGH (5+ conflicts)

Output Format

Present top 25 as markdown table:

RankNameCategoryScoreTM RiskDomainNotes
1BidDeed.AICompound90LOW✅ .aiFunction + AI clear
2Shapira Formula™Founder92LOW✅ .aiPersonal IP ownership

Special Cases

Metric/Framework Names: Emphasize Founder-based + Formula categories. High metaphor power for investor pitches.

IP Protection Focus: Favor Founder-based (personal ownership clear) and Invented (high TM strength).

Dual-Brand Strategy: Generate both umbrella + product names. Verify brand hierarchy logic.

See references/naming_best_practices.md for trademark templates and brand architecture patterns.

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