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/arn-spark-naming

This skill should be used when the user says "naming", "brand name", "name my product", "find a name", "product naming", "brand naming", "what should I call it", "name ideas", "pick a name", "naming session", "help me name this", "brainstorm names", "come up with a name", "arn

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arness
3590 skills48 agents

Claude Code

$ npx -y skills add AppsVortex/arness --skill arn-spark-naming --agent claude-code

SKILL.md

arn-spark-naming.SKILL.md
name: arn-spark-naming
description: >-
  This skill should be used when the user says "naming", "brand name",
  "name my product", "find a name", "product naming", "brand naming",
  "what should I call it", "name ideas", "pick a name", "naming session",
  "help me name this", "brainstorm names", "come up with a name",
  "arn spark naming", "arn-spark-naming", or wants to find a brand
  name for their product through strategic analysis, creative generation,
  qualitative scoring, and due diligence including domain availability
  and trademark screening.
version: 1.0.0

Arness Spark Naming

Guide a product from nameless concept to validated brand name through a structured 4-step methodology, driven by the `arn-spark-brand-strategist` agent. Produces a **naming brief** (`naming-brief.md`) in the vision directory and a **naming report** (`naming-report.md`) in the reports directory.

Prerequisites

1. Read the project's CLAUDE.md for the `## Arness` section. 2. Extract **Vision directory** and **Reports directory** paths. If no `## Arness` section exists or Arness Spark fields are missing, inform the user: "Arness Spark is not configured for this project yet. Run `/arn-brainstorming` to get started — it will set everything up automatically." Do not proceed without it. 3. Create directories if they do not exist.

Step 0: Context Gathering

Product context

Check for `<vision-dir>/product-concept.md`:

**If found:** Read and extract: vision statement, value proposition, target audience, product pillars, competitive landscape. Summarize the extracted context to the user: "Found your product concept. I'll use this as the foundation for naming."

**If not found:**

Ask (using `AskUserQuestion`):

**"No product concept found. How should I learn about your product?"** 1. **Describe your product** — Provide a description in the next message 2. **Point me to a file** — Specify a file path containing product information 3. **Explore current project** — I'll read README, package.json, and code to infer what the product does

If option 3: invoke `arn-spark-brand-strategist` in `brand-dna` mode with instructions to explore the project and summarize the product context.

Target market

Ask (using `AskUserQuestion`):

**"What is the primary target market? This determines trademark databases and languages for linguistic screening."** 1. **United States** — USPTO trademark search, English + Spanish linguistic check 2. **European Union** — EUIPO trademark search, English + French + German + Spanish + Italian 3. **United Kingdom** — IPO trademark search, English linguistic check 4. **Global / Multiple regions** — WIPO + major national databases, all major languages

Existing naming brief

Check for `<vision-dir>/naming-brief.md`:

**If found:**

Ask (using `AskUserQuestion`):

**"A naming brief already exists. How would you like to proceed?"** 1. **Resume from where I left off** — Continue from the first incomplete section 2. **Start fresh** — Preserve existing as naming-brief-previous.md and begin new

If resume: read the brief, detect which sections contain "-- Pending --" or are missing, and resume from the first incomplete step.

---

Step 1: Strategic Foundation (Brand DNA)

Invoke the `arn-spark-brand-strategist` agent in `brand-dna` mode via the Task tool, passing the model from `.arness/agent-models/spark.md` as the `model` parameter (see `plugins/arn-spark/skills/arn-spark-ensure-config/references/ensure-config.md` "Dispatch convention" for fallback). Context:

  • Product context (from product-concept.md or user input)
  • Competitive landscape (from product concept, or agent will research via WebSearch)
  • Target market

The agent returns: brand personality profile, audience vocabulary, competitor name landscape, 1-2 recommended naming categories with rationale.

Present the Brand DNA analysis to the user.

Ask (using `AskUserQuestion`):

**"Proceed with the recommended naming categories?"** 1. **Yes, proceed with [recommended categories]** (Recommended) — Use the strategist's recommendation (substitute actual category names from the Brand DNA analysis) 2. **Choose different categories** — Select naming categories manually

If option 2:

Ask (using `AskUserQuestion`, `multiSelect: true`):

**"Select naming categories to explore (select all that apply):"** 1. **Descriptive** — Names that describe what the product does (PayPal, Dropbox) 2. **Evocative** — Names that suggest a feeling or metaphor (Slack, Nike) 3. **Invented / Abstract** — Completely new words (Spotify, Google) 4. **Lexical** — Wordplay, puns, alliteration (Pinterest, Netflix)

Then prompt (free-text): "Any existing name ideas, words you love, or words you hate? These will seed the creative sprint. Type 'none' or 'skip' to continue without seeds."

Write initial `<vision-dir>/naming-brief.md` using the creative brief template: > Read `${CLAUDE_PLUGIN_ROOT}/skills/arn-spark-naming/references/creative-brief-template.md`

Populate: Context and Brand DNA sections. Mark remaining sections as "-- Pending --".

---

Step 2: Creative Sprint (The Big List)

Four generation rounds via `arn-spark-brand-strategist` in `generation` mode.

**Round 1 — Seed harvest:** Invoke agent with user's existing ideas and preferences as seeds. If no seeds, skip to Round 2.

**Round 2 — Category sprints:** Invoke agent once per selected category, requesting 50-80 candidates each. Pass the brand DNA context and dead directions. Present candidates to user after each category sprint for early feedback.

**Round 3 — Mashup round:** Invoke agent with all Round 1-2 candidates. Cross-pollinate fragments across categories. Target: 30-50 mashup candidates.

**Round 4 — User collaboration checkpoint:** Present the complete candidate list organized by category. This is a free-text conversation loop: the user marks favorites (star), flags directions to kill, and may suggest additional directions. Iterate until the user signals satisfaction.

Targe

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Questions about arn-spark-naming.

Which coding agents can use arn-spark-naming?
arn-spark-naming installs in Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and Windsurf with the skills CLI, using each agent's flag shown on this page. Flowy's auto-invocation, which fires a skill when your prompt matches, runs in Claude Code only.