NameLens

Research and stress-test open-source project names, from collision checks to launch-ready decisions.

License: MIT

NameLens is an Agent Skill for researching and stress-testing open-source project names, from collision checks to launch-ready decisions. It helps builders generate candidate names, evaluate GitHub and package namespace risk, verify language claims, and choose one name that is memorable, searchable, and ready to publish.

Why It Exists

Naming an open-source project is not only a creative task. A strong name has to survive search results, repository slugs, package registries, CLI commands, pronunciation, cross-language meaning, and future scope.

NameLens treats a name as a publishing decision, not a random suggestion.

What It Checks

  • Positioning: what the name should signal, who it serves, and what future scope it must leave open.
  • Transmission: whether people can read, say, hear, spell, type, and remember it.
  • Collisions: web search, GitHub, package registries, app stores, domains, handles, and realistic variants.
  • Language risk: verified roots, native usage, romanization, pronunciation, slang, and false etymology.
  • SEO/GEO clarity: a stable brand plus a clear category descriptor that machines and people can understand.
  • Decision quality: ranked finalists, rejected names, trade-offs, and one recommended winner.

Quick Start

Install the skill from this repository:

npx skills add geekjourneyx/namelens

The installable skill lives in skills/namelens/ so bundled references and assets are resolved relative to the skill root.

Then ask your agent to use namelens for a naming decision:

I am building a Rust CLI that finds visually similar screenshots.
Name it. The crate, command, and GitHub repo should match if possible.
Avoid cute names, verify collisions, and give me one final recommendation.

Example Prompts

Rename an open-source AI note-organizing tool.
The name should be easy to share, low-risk on GitHub and npm,
and should not rely on unverified Latin or Japanese etymology.

Compare NameLens, NameRadar, and Nomexa for an Agent Skill that researches names
for open-source projects. I need one final recommendation and exact GitHub About text.

I am building a consumer app for Japanese learners who practice shadowing from podcasts.
Explore English, Japanese, Latin, and metaphorical options, then screen obvious collisions.

What You Get

A standard NameLens report includes:

  1. A compact naming brief and assumptions.
  2. Search scope and research date.
  3. Independent naming lanes, not twenty variants of one root.
  4. A candidate matrix with pronunciation, semantic fit, collision risk, namespace fit, and naming difficulty.
  5. Top finalists with clear trade-offs.
  6. Rejected or dangerous names and why they failed.
  7. Launch-ready identity fields: display name, repository slug, package or command name, category descriptor, tagline, GitHub About text, topics, and remaining checks.

NameLens never presents preliminary research as legal or trademark clearance.

Modes

Mode Use When Output
Quick Early exploration 12-18 candidates, light collision checks, top 3
Standard Default naming decision 30-50 raw candidates, 12-20 researched finalists, one winner
Deep Public launch or commercial stakes More variants, domains, handles, app stores, local markets, and preliminary trademark screening

Project Layout

skills/
└── namelens/
    ├── SKILL.md
    ├── assets/
    │   ├── banner.svg
    │   ├── banner.png
    │   └── banner.webp
    ├── evals/
    ├── examples/
    ├── references/
    └── test-prompts.json

The skill is pure documentation. There are no runtime scripts or package dependencies in this repository.

License

MIT

Author