A structured process for naming products, companies, brands, or projects, from defining the strategy through generating, comparing, and checking name candidates.

Use it to develop names, assess their language and cultural associations, and verify whether suitable names appear to be available online.

It replaces unstructured brainstorming with criteria tied to the intended audience, advantage, meaning, sound, and availability.

namer — Skill for Claude Code and Codex by jbold

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent

npx skills add jbold/namer --skill namer

Clone the repo

git clone --depth 1 https://github.com/jbold/namer

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/jbold/namer/namer/github.svg)](https://agentmods.dev/skills/jbold/namer/namer)

Your own site

<a href="https://agentmods.dev/skills/jbold/namer/namer"><img src="https://agentmods.dev/badge/skills/jbold/namer/namer/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/jbold/namer/namer"><img src="https://agentmods.dev/badge/skills/jbold/namer/namer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 48 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,714 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00048	$0.01714
Opus 5.5	$0.00019	$0.00686
Sonnet 5.5	$0.00010	$0.00343
Haiku 4.5	$0.00005	$0.00171

Measured 2mo ago against content hash 8c5424dbd698, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

namer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

SKILL.md · 128 lines

How it starts

The opening of the file, as written. The whole thing — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Namer

Structured naming pipeline for any product, company, or brand. Uses the Diamond Framework (David Placek / Lexicon Branding) for strategy, then leverages LLM knowledge of languages, cultures, history, and sound symbolism to generate and evaluate candidates.

Pipeline: Discover → Seeds → Generate → Evaluate → Verify → Present

Step 1: Discover

Ask these 5 questions one at a time, in order:

1. What's the domain? — "What industry or category is this?" (e.g. coffee shop, developer tool, law firm, band)

2. What does winning look like? — The vision. What is this, who's it for, what does success look like?

Swiffer: "Build a mop-like device people pay a premium for. Make cleaning floors something people want to do."

3. What do we have to win? — The advantage. What assets or insights give you an edge?

Swiffer: "P&G's Pampers diaper tech — a lighter, more effective tool using absorbent pads instead of water."

4. What do we need to win? — The gaps. What's missing? What must be overcome?

Swiffer: "Avoid being seen as just another mop. People hate mopping — they need to see this as entirely new."

5. What do we need to say? — The message. What should the name communicate? What should it feel like?

Swiffer: "Logical: efficient, quick, easy. Emotional: fun, joyful, light. Should sound like a quick, satisfying action."

See references/diamond-framework.md for the full framework with case studies.

Step 2: Extract Seeds

From the user's answers, extract 30-50 seed words:

Literal seeds (~15-25):

~3-5 from domain vocabulary
~3-5 from "winning" (vision/ambition)
~3-5 from "have to win" (differentiators)
~2-3 from "need to win" (aspirations)
~3-5 from "need to say" (feeling/tone)

Evocative seeds (~15-25) — generate these yourself:

Metaphorical — words from adjacent domains (nature, mythology, architecture, music, materials). "If this product were a natural phenomenon, what would it be?"
Cross-cultural roots — Latin, Greek, Sanskrit, Japanese, Arabic roots carrying the right connotation
Sound-designed — invented syllable combos chosen for phonetic personality

Read the full file on GitHub · 128 lines

Files

What ships with it

3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

2mo ago First seen · 128 lines · 48 tokens per session scan A 8c5424dbd698

Subscribe to this mod's changes

namer is a skill published in the GitHub repository jbold/namer (5 stars, last pushed 8mo ago), licensed MIT. It adds 48 tokens to every session and 1,714 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Marketing and SEO

namer next to 6 skills from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
namerjbold/namer	Skill	5	8mo ago	MIT	A	48	Claude Code, Codex
imagegenopenai/codex	Skill	134k	today	Apache-2.0	A	113	Codex
playwright-climicrosoft/playwright	Skill	99k	yesterday	Apache-2.0	A	19	Claude Code
local-ai-agentsmicrosoft/ai-agents-for-beginners	Skill	79k	4d ago	MIT	A	200	Claude Code, Codex
systematic-debuggingobra/superpowers	Skill	314k	3d ago	MIT	A	21	Claude Code
next-cache-components-adoptionvercel/next.js	Skill	143k	yesterday	MIT	A	95	Claude Code
next-partial-prefetching-adoptionvercel/next.js	Skill	143k	yesterday	MIT	A	103	Claude Code