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 OneWave-AI/claude-skills --skill brand-voice-analyzergit clone --depth 1 https://github.com/OneWave-AI/claude-skillsWrote 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/onewave-ai/claude-skills/brand-voice-analyzer)<a href="https://agentmods.dev/skills/onewave-ai/claude-skills/brand-voice-analyzer"><img src="https://agentmods.dev/badge/skills/onewave-ai/claude-skills/brand-voice-analyzer/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/onewave-ai/claude-skills/brand-voice-analyzer"><img src="https://agentmods.dev/badge/skills/onewave-ai/claude-skills/brand-voice-analyzer.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 | $0.00068 | $0.00818 |
| Opus 5 | $0.00034 | $0.00409 |
| Sonnet 5 | $0.00014 | $0.00164 |
| Haiku 4.5 | $0.00007 | $0.00082 |
Grade A, and why
brand-voice-analyzer 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 13d 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 — 59 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Brand Voice Analyzer
Ingest a company's existing content, reverse-engineer the voice behind it, produce a definitive brand voice guide any writer can follow, and review new content against an established guide.
Contents
references/voice-dimensions.md-- the seven-axis tone spectrum, vocabulary, sentence, personality, audience, and formatting dimensions to extractreferences/guide-template.md-- required sections, quality standards, and pre-delivery checklist forbrand-voice-guide.mdreferences/review-mode.md-- process and output format for scoring content against a guidereferences/metrics.md-- quantitative and qualitative analysis techniques and citation standardsreferences/edge-cases.md-- handling for thin corpora, multiple voices, regulated industries, rebrands, plus interaction patterns
Workflow: Create a New Voice Guide
- Ask which content sources are available (URLs, files, directories, pasted text).
- Ask about any known brand attributes, values, or existing guidelines.
- Collect the corpus. Pull URLs with WebFetch, locate files with Glob/Read, find public content with WebSearch. Gather website copy, 5-10 blog posts, email campaigns, social posts, sales collateral, and support content. Document each source and its word count.
- Confirm corpus size. Require at least 3,000 words across 2+ content types. If smaller, flag the limitation and mark affected findings as lower confidence.
- Run the full voice extraction across every dimension in
references/voice-dimensions.md, citing source examples per the standards inreferences/metrics.md. - Present a summary of findings for validation before generating the guide.
- Generate the complete
brand-voice-guide.mdfollowingreferences/guide-template.md. Verify it against that checklist before delivery. - Offer to review a sample piece of content against the new guide.
Workflow: Review Content
- Locate or ask for the
brand-voice-guide.md. - Read the content to be reviewed.
- Run the review process and produce the scored output defined in
references/review-mode.md. - Present findings with actionable, guide-referenced fixes.
What ships with it
5 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.
- 13d ago First seen · 59 lines · 68 tokens per session scan A 133bda2d6800
brand-voice-analyzer is a skill published in the GitHub repository OneWave-AI/claude-skills (291 stars, last pushed 1mo ago), licensed MIT. It adds 68 tokens to every session and 818 once invoked, about $0.0003 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 2026-08-30.
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