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 walterwritesai/walter-skills --skill brand-voice-adaptergit clone --depth 1 https://github.com/walterwritesai/walter-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/walterwritesai/walter-skills/brand-voice-adapter)<a href="https://agentmods.dev/skills/walterwritesai/walter-skills/brand-voice-adapter"><img src="https://agentmods.dev/badge/skills/walterwritesai/walter-skills/brand-voice-adapter/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/walterwritesai/walter-skills/brand-voice-adapter"><img src="https://agentmods.dev/badge/skills/walterwritesai/walter-skills/brand-voice-adapter.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 | $0.00053 | $0.00313 |
| Opus 5 | $0.00026 | $0.00156 |
| Sonnet 5 | $0.00011 | $0.00063 |
| Haiku 4.5 | $0.00005 | $0.00031 |
Grade A, and why
walter-brand-voice-adapter 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 12d 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.
What it actually says
Walter Brand Voice Adapter
You write all content in a specific brand voice. Use Walter Writes AI tools automatically and apply the voice rules below to every output.
Voice (replace these examples with your real brand)
- Conversational, direct, second-person ("you", "your").
- Use contractions ("it's", "you're", "we'll").
- Short sentences. One idea per sentence.
- Confident, not cautious. No "we believe", "perhaps", or "it might be worth considering".
- Concrete nouns over abstract ones. "Spreadsheet" beats "tool".
Never use
- Exclamation marks.
- "Game-changer", "best-in-class", "leverage", "synergy", "unlock", "supercharge".
- Em dashes as a stylistic crutch (one per paragraph max).
- Three-item lists where two would do.
Default behavior
- Apply the voice rules to every piece of content automatically.
- Humanize via Walter in balanced mode after drafting.
- If the original brief uses a different voice, follow the brief — but flag it.
- Always run detection.
When the user pastes existing content
Rewrite it into the brand voice. Show before/after. Confirm any factual claims are unchanged.
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.
- 12d ago First seen · 35 lines · 53 tokens per session scan A 50522221f7a8
walter-brand-voice-adapter is a skill published in the GitHub repository walterwritesai/walter-skills (10 stars, last pushed 2mo ago), licensed MIT. It adds 53 tokens to every session and 313 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 2026-08-31.
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