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pdf-master-translatorPDF master translator 文档

Agent Skill

pdf-master-translator 用于整理文档、README、Markdown 和说明材料,适合在 OpenClaw 中需要把零散信息整理成结构清晰的文档时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

8,486

周安装

340

GitHub Stars

公开资料未说明

下载量

2,747
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:pdf-master-translator(PDF master translator 文档)
来源仓库:https://github.com/lingqing/pdf-master-translator
安装命令:
openclaw skills install pdf-master-translator
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install pdf-master-translator

简介

pdf-master-translator 是多代理管道,专译含图像与公式的复杂 PDF。

  • 适用于工程图纸、科研论文等高保真翻译需求。pdf-master-translator 属于效率类 Skill,可作为该场景下的辅助能力补充。
  • 支持多语种互译与版面重建,保持专业术语准确性。
  • 使用前需确认源语言与目标语言组合是否被支持。
  • 建议分段提交大文件,避免单次处理超时或内存溢出。

SKILL.md

name
pdf-master-translator
description
A highly robust, multi-agent pipeline for translating and reconstructing complex, image-heavy, or scanned PDF documents (especially engineering, scientific, or military specs). Use this skill when dealing with PDFs that contain complex layouts, dense tables, mathematical formulas (LaTeX), or when previous translation attempts resulted in broken layouts, missing figures, "hallucinated" translations, or corrupted text. It uses a "mask-and-fill" approach, holographic context injection, and SVG math rendering to ensure zero information loss and strict visual fidelity.

PDF Master Translator (V10 Architecture)

This skill provides a battle-tested, "bulletproof" pipeline for translating complex PDF documents. It was forged from extensive trial and error on NASA engineering specifications.

Do NOT attempt to use simple OCR or zero-shot LLM translation for complex engineering documents. They will fail. Use the translator_engine_v10.py script provided in this skill.

Core Capabilities & The V10 Pipeline

This skill relies on a Python script (scripts/translator_engine_v10.py) that implements a specific, multi-agent workflow:

  1. Layout & Physical Isolation (Masking):

- Never ask an LLM to "ignore the picture and translate the text" on a messy scan. - The pipeline first detects figures and tables. - It physically whites out (masks) these regions on a temporary image. - The "clean" image is sent for translation, eliminating visual hallucinations. - Original figures are extracted, converted to Base64, and safely appended to the final HTML/PDF.

  1. Holographic Context Injection:

- Masking creates fragmented sentences around the masked areas. - To prevent the translation Agent from producing out-of-context or broken translations, the pipeline injects the raw, unformatted text stream of the entire page as a reference dictionary. The Agent uses this context to seamlessly bridge the visual gaps.

  1. Protocol Downgrade (XML over JSON):

- Forcing LLMs to output thousands of words of Markdown inside a strict JSON structure is fragile and prone to escaping errors. - The engine enforces simple XML tags (<HEADER>, <BODY>, <FOOTER>) for structural routing.

  1. Strict Math & Symbol Rendering:

- Standard PDF renderers (like WeasyPrint) cannot execute JavaScript (MathJax). - The script uses regex to intercept all LaTeX ($...$ or $$...$$) and calls an external API (math.vercel.app) to render them as high-quality, embeddable SVG images. - The Prompt strictly mandates the format **$Variable$**: Description for symbol glossaries, ensuring visual consistency.

  1. Terminal Defense (Sanity Cleaner):

- The final step before PDF generation is a regex sweep to remove any leaked LLM artifacts (like ```markdown wrappers) or error placeholders (like RetryError[]) that might have survived the pipeline.

Usage Instructions

To use this skill, execute the translator_engine_v10.py script.

Prerequisites

Ensure the required dependencies are installed (typically handled via uv run if inline metadata is used) and the Gemini API key is set.

export GEMINI_API_KEY="your_api_key_here"
# If a proxy is required for your network:
export HTTPS_PROXY="http://127.0.0.1:10809" 

Execution

Run the script, providing the path to the target PDF and the specific page range.

uv run ~/.npm-global/lib/node_modules/openclaw/skills/pdf-master-translator/scripts/translator_engine_v10.py /path/to/target.pdf --start <start_page> --end <end_page>

Important Operational Rules:

  • Always specify --start and --end explicitly.
  • For very large documents (>20 pages), it is highly recommended to run this using nohup ... & in the background, as the multi-agent cross-checking and API rate-limiting sleep cycles make this a long-running process.

Output

The script will generate a new PDF named [OriginalName]_V10_FINAL_P[start]-[end].pdf in the current working directory.

This PDF will feature:

  • A clear --- Page X --- divider for continuous reading.
  • Consistent Header and Footer markdown tables.
  • SVG-rendered math formulas.
  • A dedicated [ 原文图表/示意图 ] section at the bottom of relevant pages containing the extracted original diagrams.
  • (If applicable) A [ 图例符号说明 ] section containing translations of text found *inside* the diagrams.

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

89.34%
按下载量换算2,454

安全审计

VirusTotal

通过

ClawScan

可疑

Static analysis

通过

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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