Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add AppsVortex/arness/plugin install arn-sparkWrote 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.
[](https://agentmods.dev/skills/appsvortex/arness/arn-spark-naming)<a href="https://agentmods.dev/skills/appsvortex/arness/arn-spark-naming"><img src="https://agentmods.dev/badge/skills/appsvortex/arness/arn-spark-naming/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.
<a href="https://agentmods.dev/skills/appsvortex/arness/arn-spark-naming"><img src="https://agentmods.dev/badge/skills/appsvortex/arness/arn-spark-naming.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00122 | $0.03551 |
| Opus 5.5 | $0.00049 | $0.01420 |
| Sonnet 5.5 | $0.00024 | $0.00710 |
| Haiku 4.5 | $0.00012 | $0.00355 |
Grade A, and why
arn-spark-naming 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 today.
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.
How it starts
The opening of the file, as written. The whole thing — 276 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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
- Read the project's CLAUDE.md for the
## Arnesssection. - Extract Vision directory and Reports directory paths. If no
## Arnesssection exists or Arness Spark fields are missing, inform the user: "Arness Spark is not configured for this project yet. Run/arn-brainstormingto get started — it will set everything up automatically." Do not proceed without it. - 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?"
- Describe your product — Provide a description in the next message
- Point me to a file — Specify a file path containing product information
- 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."
- United States — USPTO trademark search, English + Spanish linguistic check
- European Union — EUIPO trademark search, English + French + German + Spanish + Italian
- United Kingdom — IPO trademark search, English linguistic check
- Global / Multiple regions — WIPO + major national databases, all major languages
What ships with it
7 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.
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.
- today First seen · 276 lines · 122 tokens per session scan A b30cb5ff851a
arn-spark-naming is a skill published in the GitHub repository AppsVortex/arness (33 stars, last pushed today), licensed MIT. It adds 122 tokens to every session and 3,551 once invoked, about $0.0005 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 2026-10-25.
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