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.
npx skills add J-StaR-Films-Studios/VibeCode-Protocol-Suite --skill global-brand-namergit clone --depth 1 https://github.com/J-StaR-Films-Studios/VibeCode-Protocol-SuiteWrote 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/j-star-films-studios/vibecode-protocol-suite/global-brand-namer)<a href="https://agentmods.dev/skills/j-star-films-studios/vibecode-protocol-suite/global-brand-namer"><img src="https://agentmods.dev/badge/skills/j-star-films-studios/vibecode-protocol-suite/global-brand-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.
<a href="https://agentmods.dev/skills/j-star-films-studios/vibecode-protocol-suite/global-brand-namer"><img src="https://agentmods.dev/badge/skills/j-star-films-studios/vibecode-protocol-suite/global-brand-namer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00130 | $0.01413 |
| Opus 5 | $0.00065 | $0.00707 |
| Sonnet 5 | $0.00026 | $0.00283 |
| Haiku 4.5 | $0.00013 | $0.00141 |
Grade A, and why
global-brand-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 8d 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.
How it starts
The opening of the file, as written. The whole thing — 120 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Global Brand Namer
Generate premium, cross-culturally resonant brand names by mining non-English vocabulary and pairing with strategic domain modifiers. This skill transforms generic naming sessions into systematic linguistic exploration.
Core Naming Principles
- Phonetic Fluidity - The word must be easily pronounceable by an English-speaking audience without phonetic training. Avoid heavy consonant clusters, tonal requirements, or characters that don't transliterate cleanly.
- Domain Viability - Assume all raw, single words (e.g., Takumi, Agbara) are squatted. Always pair the base word with a strategic modifier. See
references/saas-modifiers.md. - Syllabic Brevity - Target 2-3 syllables maximum for the base word. One-syllable words work if they're distinctive.
- Semantic Depth - The meaning behind the word should resonate with the product's purpose. A name with real meaning creates richer brand storytelling.
- Cross-Lingual Safety - Verify the transliterated word doesn't mean something offensive in major world languages (English slang, Spanish, French, Portuguese, Mandarin).
Workflow
Step 1: Distill the Core Concept
Extract 2-4 English keywords capturing the product's function, feeling, or identity.
Prompting questions:
- What does the product DO? (build, connect, analyze, create)
- What FEELING should it evoke? (speed, trust, power, calm)
- Who is the audience? (developers, creators, enterprise, consumers)
- What's the competitive landscape? (crowded SaaS, niche tool, consumer app)
Example: A developer workflow tool might yield: build, flow, craft, forge
Step 2: Linguistic Translation & Exploration
Translate concepts across diverse language families. Select language categories that match the project's aesthetic.
Reference: Load references/language-matrices.md for full language-to-aesthetic mapping.
Quick selection guide:
| Project Vibe | Best Language Families |
|---|---|
| Dev tools / Infrastructure | Japanese, Nordic, Latin, German |
| Creative / AI / Workflows | Yoruba, Sanskrit, Maori, Swahili |
| Minimalist SaaS / Analytics | Mandarin (Pinyin), Esperanto, Finnish |
| Community / Social | Zulu, Hawaiian, Portuguese, Tagalog |
| Security / Trust | Arabic, Norse, Latin, Greek |
What ships with it
2 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.
- 8d ago First seen · 120 lines · 130 tokens per session scan A c605c86620c7
global-brand-namer is a skill published in the GitHub repository J-StaR-Films-Studios/VibeCode-Protocol-Suite (24 stars, last pushed yesterday), licensed ISC. It adds 130 tokens to every session and 1,413 once invoked, about $0.0006 per session on Opus 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 2026-09-03.
Other skills, from other repositories
happiness-skill
A Chinese-language guide to happiness based on reducing unmet wants, focusing on the present, and treating happiness as a trainable skill.
setup-matt-pocock-skills
A setup skill that configures engineering skills for a repository, including its issue tracker, labels, and documentation layout. A repository is the project folder managed by version control.
frontend-design
A design guide for building polished web interfaces such as pages, dashboards, forms, navigation, and reusable UI components. It covers HTML, CSS, JavaScript, and common frontend frameworks.
alterlab-cobrapy
Build and analyze genome-scale constraint-based metabolic models with COBRApy — flux balance analysis (FBA), flux variability analysis (FVA), gene and reaction knockouts, flux sampling, and SBML model I/O. Use when simulating metabolic networks, predicting growth or knockout phenotypes, or running systems-biology and…
alterlab-depmap
Query the Cancer Dependency Map (DepMap) for cancer cell line gene dependency scores (CRISPR Chronos), drug sensitivity data, and gene effect profiles. Use when identifying cancer-specific genetic vulnerabilities, finding synthetic lethal interactions, checking whether a gene is essential in given cell lines, or…
alterlab-qutip
Simulates open quantum systems with QuTiP, the Quantum Toolbox in Python, solving Lindblad master equations (mesolve), Monte Carlo trajectories (mcsolve), and unitary dynamics (sesolve). Use when studying master-equation or Lindblad dynamics, decoherence, dissipation, quantum optics, cavity QED, or open-system time…