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 hogan-tech/brand-loom --skill bilingualgit clone --depth 1 https://github.com/hogan-tech/brand-loomWrote 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/hogan-tech/brand-loom/bilingual)<a href="https://agentmods.dev/skills/hogan-tech/brand-loom/bilingual"><img src="https://agentmods.dev/badge/skills/hogan-tech/brand-loom/bilingual.svg" alt="Measured on agentmods" 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 | $0.00042 | $0.00403 |
| Opus 5 | $0.00021 | $0.00201 |
| Sonnet 5 | $0.00008 | $0.00081 |
| Haiku 4.5 | $0.00004 | $0.00040 |
Grade A, and why
bilingual 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.
What it actually says
Bilingual Translator (EN ↔ zh-TW)
Voice-preserving translation between English and Traditional Chinese. Preserves brand tone, audience targeting, and phrase preferences across languages.
Quick start
- CLI:
brand-loom run bilingual --text "Ship it, then iterate." --target-locale zh-TW - Python API:
run_skill("bilingual", "Ship it.", target_locale="zh-TW")
Features
- Voice-preserving rewrite (not word-level translation)
- Supports
preserve_termsto keep brand names, acronyms verbatim - Full
brand_contextsupport (tone, audience, do/avoid phrases) - Returns unchanged if source = target locale
Multi-language support beyond EN/zh-TW (auto-detection, 10+ locales, continuous voice alignment) lives in hosted Neoxra.
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 · 33 lines · 42 tokens per session scan A f513f3b42aa9
bilingual is a skill published in the GitHub repository hogan-tech/brand-loom (22 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 42 tokens to every session and 403 once invoked, about $0.0002 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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deutsch-englisch-digitale-inhalte-handbuch
Für Deutsch Englisch AGB: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Schnittstellenkarte mit Zuständigkeits- und Nachweisfragen. Fachgebiet: AGB-Recht-Prüfer. Route: deutsch-englisch-digitale-inhalte-handbuch.
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Für Deutsch Englisch AGB: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Schnittstellenkarte mit Zuständigkeits- und Nachweisfragen. Fachgebiet: AGB-Recht-Prüfer. Route: deutsch-englisch-agb.