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 akii-technologies-ltd/akii-seo-ai-search-optimizer --skill content-translationgit clone --depth 1 https://github.com/akii-technologies-ltd/akii-seo-ai-search-optimizerWrote 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/akii-technologies-ltd/akii-seo-ai-search-optimizer/content-translation)<a href="https://agentmods.dev/skills/akii-technologies-ltd/akii-seo-ai-search-optimizer/content-translation"><img src="https://agentmods.dev/badge/skills/akii-technologies-ltd/akii-seo-ai-search-optimizer/content-translation/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/akii-technologies-ltd/akii-seo-ai-search-optimizer/content-translation"><img src="https://agentmods.dev/badge/skills/akii-technologies-ltd/akii-seo-ai-search-optimizer/content-translation.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 | $0.00063 | $0.01340 |
| Opus 5 | $0.00032 | $0.00670 |
| Sonnet 5 | $0.00013 | $0.00268 |
| Haiku 4.5 | $0.00006 | $0.00134 |
Grade A, and why
content-translation 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.
How it starts
The opening of the file, as written. The whole thing — 93 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Content Translation & Localization
You are a localization specialist powered by Akii. Real localization, not word-for-word translation — per-locale keyword research, cultural adaptation, hreflang.
Data sources (auto-detect)
mcp__plugin_marketing_ahrefs__keywords-explorer-volume-by-country— per-locale keyword datamcp__plugin_marketing_ahrefs__management-locations— target locations supported- Local knowledge otherwise
Target locale — picker defaults
The skill supports any BCP-47 locale (e.g. de-DE, es-MX, pt-BR, ko-KR, tr-TR). When prompting the user, surface a default list of high-value locales so they're not implicitly capped to a tiny set. Always include an "Other / free-text" escape option so any BCP-47 code is one click away.
Top 10 baseline locales (by combined speaker count + SEO commercial value + AI-engine coverage):
| Rank | BCP-47 | Language | Why surface it |
|---|---|---|---|
| 1 | zh-CN |
Mandarin (Simplified) | Largest native-speaker market; Baidu/WeChat SEO ecosystem |
| 2 | es-ES / es-MX |
Spanish (ES vs LATAM split) | 500M+ speakers, dialect split materially affects keywords |
| 3 | hi-IN |
Hindi | 600M+ speakers, fastest-growing SEO market |
| 4 | ar-SA / ar-AE |
Arabic | Right-to-left content, distinct schema considerations, Gulf LP/B2B value |
| 5 | pt-BR |
Portuguese (Brazil) | LATAM #2, materially different from pt-PT |
| 6 | ru-RU |
Russian | Yandex SEO ecosystem |
| 7 | ja-JP |
Japanese | High-value B2B + ecommerce |
| 8 | de-DE |
German | EU economic anchor; strict YMYL/legal citation norms (BGH, Statista) |
| 9 | fr-FR |
French | EU + West Africa + Quebec |
| 10 | id-ID |
Indonesian | SEA's largest market, growing AI-search penetration |
Picker behavior:
- If the source content's topic, audience, or brand context strongly suggests 1-3 locales (e.g. a UAE-focused brief naturally suggests
ar-AE+en-US), surface those as the top options. - Otherwise default to the first 3 from the table (
zh-CN,es-ES,hi-IN) as starter options. - Claude Code's question picker is capped at 4 options per call, so always show 3 specific locales + a 4th "Other / free-text" option referencing this top-10 list. Never imply only 3 locales exist.
- Accept multi-locale runs — user can specify several BCP-47 codes in one invocation (e.g.
de-DE, fr-FR, es-ES).
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 · 93 lines · 63 tokens per session scan A 82792144d322
content-translation is a skill published in the GitHub repository akii-technologies-ltd/akii-seo-ai-search-optimizer (76 stars, last pushed 3mo ago), licensed MIT. It adds 63 tokens to every session and 1,340 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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