arn-spark-naming

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.

Target: 200+ total candidates across all rounds.

Update naming-brief.md with Creative Sprint Results section (generation stats, candidates by category, starred favorites, dead directions).

Step 3: Qualitative Filter (Six Senses)

Load the scoring methodology:

Read ${CLAUDE_PLUGIN_ROOT}/skills/arn-spark-naming/references/naming-methodology.md

Invoke the arn-spark-brand-strategist agent in scoring 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: full candidate list, user-starred favorites, dead directions.

Pass 1: Agent filters 200+ candidates to 30-40 by removing obvious duds (unpronounceable, too long, too similar, offensive, dead directions). User-starred names always survive Pass 1.

Pass 2: Agent scores each surviving candidate on the Six Senses (1-5 each):

1. Appearance — visual punch, letter count
2. Sound — euphony, Phone Test
3. Meaning — associations, connotations
4. Memorability — stickiness, alliteration
5. Function — verbability, typability, handle-fit
6. Scalability — expansion headroom

Present the scored table sorted by total score (6-30).

Prompt (free-text): "Select 5-8 finalists for due diligence. You can pick from the top of the table, or choose names you like regardless of score."

Update naming-brief.md with Qualitative Filter Results section.

Step 4: Cold Shower (Due Diligence)

4a — Domain Availability

Load the WHOIS/RDAP server reference:

Read ${CLAUDE_PLUGIN_ROOT}/skills/arn-spark-naming/references/whois-server-map.md

How it works: Both scripts use RDAP (the modern IETF standard) as the primary lookup method, with port-43 WHOIS and system whois as built-in fallbacks. The fallback chain per domain is: RDAP → port-43 WHOIS → system whois → manual URL. The scripts handle this automatically — no manual fallback logic needed.

Environment detection (priority order):

1. Check Python: run python3 --version. If available, use ${CLAUDE_PLUGIN_ROOT}/skills/arn-spark-naming/scripts/whois-check.py.
2. Check Node.js: run node --version. If available, use ${CLAUDE_PLUGIN_ROOT}/skills/arn-spark-naming/scripts/whois-check.js.
3. Neither available: skip automated checking. Present manual fallback URLs (https://www.whois.com/whois/[domain]) for each domain.

Note: System whois is NOT required — both scripts have it as a built-in last-resort fallback (gracefully skipped on Windows wh