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 LienJack/learn-agent --skill translategit clone --depth 1 https://github.com/LienJack/learn-agentWrote 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/lienjack/learn-agent/translate)<a href="https://agentmods.dev/skills/lienjack/learn-agent/translate"><img src="https://agentmods.dev/badge/skills/lienjack/learn-agent/translate/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/lienjack/learn-agent/translate"><img src="https://agentmods.dev/badge/skills/lienjack/learn-agent/translate.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 | $0.00024 | $0.00684 |
| Opus 5.5 | $0.00010 | $0.00274 |
| Sonnet 5.5 | $0.00005 | $0.00137 |
| Haiku 4.5 | $0.00002 | $0.00068 |
Grade A, and why
translate 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 1mo 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
自动翻译入口 Skill
本 skill 只能通过显式引用本文件路径触发，不依赖全局安装、symlink 或 $skill-name 自动发现。
输入要求
- 用户应提供一个或多个中文 Markdown 文章路径，或显式提供
--pipeline claude-code-series处理系列配置。 - 用户可以用自然语言说明目标语言，例如“翻译成英文”“做日语版”“生成 Japanese 版本”。
- 用户也可以显式传入
--language en或--language ja；显式参数优先级最高。 - 如果没有文章路径且没有 pipeline 配置，先要求用户补充，不要猜测最近文件。
语言识别规则
按以下顺序判断目标语言：
- 如果输入包含
--language en、--lang en、language=en或lang=en，选择英文。 - 如果输入包含
--language ja、--lang ja、language=ja或lang=ja，选择日语。 - 如果用户说“英文”“英语”“English”“EN”“英译”，选择英文。
- 如果用户说“日语”“日文”“日本語”“Japanese”“JA”“Zenn”，选择日语。
- 如果同时出现英文和日语信号，或没有任何语言信号，必须先向用户澄清，不要自动选择。
澄清时给出编号选项并等待用户回复：
- 英文
- 日语
执行流程
- 阅读
translate/README.md、translate/workflows/claude-code-series.md和translate/workflows/gpt-codex-cli.md。 - 根据语言识别规则确定目标语言。
- 如果目标语言是英文，阅读并执行
translate/skills/translate-en/SKILL.md。 - 如果目标语言是日语，阅读并执行
translate/skills/translate-ja/SKILL.md。 - 保留用户传入的
--pipeline、文章路径和其他非语言参数；转交给对应语言 skill。 - 不在本入口中直接调用模型翻译、不发布到外部平台、不处理图片资产；正文真实翻译由对应语言 skill 通过 GPT Codex (
codex exec) 执行，图片资产继续使用translate/skills/translate-assets/SKILL.md。
安全边界
- 本入口只做语言识别和 skill 路由，不复制英文/日语翻译规则。
- 真实翻译前仍必须遵守对应语言 skill 的 dry-run、摘要展示和用户确认流程。
- 正文真实翻译只使用 GPT Codex，不调用 Claude Code 或
claudeCLI。 - 运行记录不得保存 API key、cookie、token 或完整私密响应。
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.
- 1mo ago First seen · 48 lines · 24 tokens per session scan A d20feac5c722
translate is a skill published in the GitHub repository LienJack/learn-agent (25 stars, last pushed 3mo ago), licensed MIT. It adds 24 tokens to every session and 684 once invoked, about $0.0001 per session on Opus 5.5. 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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