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 kaixindelele/wechat_agent_bridge_skills --skill babeldoc-transgit clone --depth 1 https://github.com/kaixindelele/wechat_agent_bridge_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/kaixindelele/wechat_agent_bridge_skills/babeldoc-trans)<a href="https://agentmods.dev/skills/kaixindelele/wechat_agent_bridge_skills/babeldoc-trans"><img src="https://agentmods.dev/badge/skills/kaixindelele/wechat_agent_bridge_skills/babeldoc-trans/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/kaixindelele/wechat_agent_bridge_skills/babeldoc-trans"><img src="https://agentmods.dev/badge/skills/kaixindelele/wechat_agent_bridge_skills/babeldoc-trans.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 | $0.00109 | $0.00816 |
| Opus 5 | $0.00055 | $0.00408 |
| Sonnet 5 | $0.00022 | $0.00163 |
| Haiku 4.5 | $0.00011 | $0.00082 |
Grade A, and why
babeldoc-trans 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
BabelDOC 论文翻译
基于 BabelDOC 的论文 PDF 翻译封装。智能版式分析 + 公式保护 + 术语自动提取，输出自动以中文标题命名。
触发条件
- 用户发送 arxiv 链接（
https://arxiv.org/abs/xxxx.xxxxx或https://arxiv.org/pdf/xxxx.xxxxx） - 用户发送 arxiv ID（如
2412.13211） - 用户上传或指定 PDF 文件路径
- 用户说"翻译这篇论文"、"translate this paper"等
工作流程
步骤 1：获取 SKILL 路径
确定本 skill 的安装路径（即包含此 SKILL.md 的目录），用于定位 scripts/translate.py。
步骤 2：执行翻译
python {SKILL_DIR}/scripts/translate.py "<输入>" --output-dir /tmp/babeldoc_output
输入可以是：
- arxiv URL：
https://arxiv.org/abs/2412.13211 - arxiv PDF URL：
https://arxiv.org/pdf/2412.13211 - arxiv ID：
2412.13211 - 本地 PDF 路径：
/path/to/paper.pdf
步骤 3：返回结果
脚本最后会打印 [DONE] {JSON}，包含：
title_en/title_zh— 英文/中文标题output_pdf— 最终 PDF 绝对路径（已以中文标题命名）size_kb— 文件大小
将翻译后的 PDF 文件发送给用户。
常用参数
| 参数 | 说明 | 默认值 |
|---|---|---|
--output-dir |
PDF 输出目录 | /tmp/babeldoc_output |
--pages |
只翻译指定页，如 1-5 |
全部 |
--qps |
翻译并发 QPS | 8 |
--dual |
额外输出双语对照 PDF | off |
--model |
OpenAI 模型 | gpt-4o-mini |
--api-base |
API base URL | https://api.bltcy.ai/v1 |
--api-key |
API key | 读取 $BABELDOC_API_KEY |
环境变量
| 变量 | 说明 | 必须 |
|---|---|---|
BABELDOC_API_KEY |
OpenAI 兼容 API key | 是 |
BABELDOC_API_BASE |
API base URL | 否（默认 https://api.bltcy.ai/v1） |
BABELDOC_MODEL |
模型名 | 否（默认 gpt-4o-mini） |
安装依赖
首次使用前运行：
bash {SKILL_DIR}/scripts/setup.sh
详细文档
更多参数说明、性能参考和常见问题排查，请查阅 references/usage_guide.md。
What ships with it
4 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.
- 12d ago First seen · 74 lines · 109 tokens per session scan A 348a46b962c5
babeldoc-trans is a skill published in the GitHub repository kaixindelele/wechat_agent_bridge_skills (20 stars, last pushed 4mo ago), licensed MIT. It adds 109 tokens to every session and 816 once invoked, about $0.0005 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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