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Pdf Translate

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L27z18328742
pdf-translate

Translate English PDF documents (especially academic papers) into Chinese using PDFMathTranslate-next (pdf2zh), producing a monolingual Chinese PDF and a bilingual side-by-side PDF with formulas, figures, and layout preserved. Automatically installs the pdf2zh_next environment via uv and reuses the model/API the user already configured in Codex or Claude Code (any OpenAI-compatible gateway), falling back to the free SiliconFlow service when no key is present. Use this skill whenever the user wants to translate a PDF to Chinese (or another language), translate a paper/论文, produce a bilingual PDF, or mentions pdf2zh / PDFMathTranslate — even if they don't name the tool explicitly. Proactively invoke this skill (do not translate manually) whenever a PDF translation task appears.

Overview

PublisherL27z18328742
Repositorypdf-translate
Skill namepdf-translate
Stars
73
Forks
6
Bundled files
4
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 4 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by L27z18328742 on GitHub. Read the source before you install it.

Installation

Install the Pdf Translate AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/L27z18328742/pdf-translate/tree/main
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/L27z18328742/pdf-translate.git \
  .claude/skills/pdf-translate
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Pdf Translate in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Pdf Translate on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Pdf Translate is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

PDF Translate (English → Chinese)

This skill translates PDF documents using PDFMathTranslate-next (pdf2zh_next), the BabelDOC-based translator that preserves formulas, charts, table of contents, and page layout. It produces two files per input:

  • *-mono.pdf — monolingual translated PDF (Chinese only)
  • *-dual.pdf — bilingual PDF (original + translation, side by side or alternating)

Why this skill exists

Translating an academic PDF well requires preserving math, figures, and layout — something plain LLM translation can't do. pdf2zh_next handles that, but it has a non-trivial install (Python 3.12, model assets) and many engine options. This skill automates the environment setup and picks a translation engine that reuses credentials the user already has, so translation "just works" without manual configuration.

Workflow

Run the setup script first (installs pdf2zh_next if missing, verifies it), then the translate script (detects the best engine and runs the translation). Both scripts are idempotent.

Subsequent runs are fast. Once pdf2zh_next is installed and the model assets are downloaded (after the first successful translation), setup.sh becomes a silent sub-second no-op — it detects the install and the ~/.cache/babeldoc/models cache and returns immediately without spawning a Python import or re-downloading anything. Re-running it on every invocation is cheap and safe; you do not need to track whether setup has happened before.

Step 1 — Ensure the environment is ready

bash
bash ~/.claude/skills/pdf-translate/scripts/setup.sh

This installs pdf2zh_next via uv tool install --python 3.12 pdf2zh-next (the project requires Python ≥3.10,<3.14; 3.12 is the documented recommendation) and confirms it is on PATH. It is fast and safe to re-run. The first real translation downloads layout/translation model assets (DocLayout-YOLO + fonts, ~hundreds of MB) into ~/.cache/babeldoc/ — tell the user the first run is slow because of this one-time download. The setup and translate scripts detect this cache and skip the "slow first run" messaging once the models are present.

Step 2 — Translate

bash
bash ~/.claude/skills/pdf-translate/scripts/translate.sh "<input.pdf>" [options]

The script auto-detects a translation engine:

  1. ClaudeCode (default when claude CLI is available) — detects if the user is running from Claude Code by checking for the claude CLI on PATH. Uses the exact model Claude Code is configured to use (resolved via ANTHROPIC_DEFAULT_SONNET_MODEL, etc.). This is the default when working in Claude Code, so the translation uses the same model ecosystem the user is already in. Note: it spawns one claude -p subprocess per text segment, so it is slower than the OpenAI engine.
  2. OpenAI-compatible (fallback when API key exists) — used when claude CLI is not found but OPENAI_API_KEY is set. Reuses the model configured for Codex: reads base_url + model from ~/.codex/config.toml and the API key from OPENAI_API_KEY. Fast (HTTP, high concurrency), ideal for full papers.
  3. SiliconFlowFree (zero-config fallback) — used when neither claude CLI nor API key is detectable. The project's free GLM-4-9B service; needs no key. Note: file content is forwarded through the project maintainer's server.

Override detection with flags: --engine openai|siliconflowfree|claudecode, --model <name>, --base-url <url>, --api-key <key>.

Common options:

  • --output <dir> — output directory (default: an output/ folder next to the input PDF)
  • --pages "1-5,8" — translate only some pages
  • --lang-in en --lang-out zh-CN — language codes (defaults: en → zh-CN)
  • --qps N --pool-max-workers N — concurrency tuning (see references/advanced.md)
  • --no-dual / --no-mono — suppress one of the two outputs
  • Pass any other pdf2zh_next flag through with -- <flag> <value>

Step 3 — Report results

After the script finishes, it prints the paths of the generated *-mono.pdf and *-dual.pdf. Tell the user where these files are (relative to the input), open/preview them if asked, and note the engine + model that was used. If the user wants different quality or speed, suggest overrides (see references/advanced.md).

Default behavior choices (and how to change them)

  • Source/target language: English → Simplified Chinese (en → zh-CN). Override with --lang-in / --lang-out. Full language code list is in references/advanced.md.
  • Engine: ClaudeCode when claude CLI is on PATH (default in Claude Code), else OpenAI-compatible when a key is found, else SiliconFlowFree. Use --engine openai to force the OpenAI engine even from Claude Code. The claudecode engine reuses Claude Code's configured model; the OpenAI engine reuses the model named in ~/.codex/config.toml.
  • Model: for the openai engine, the model from ~/.codex/config.toml; for claudecode, sonnet (resolved by Claude Code to the user's configured model). Reasoning models (e.g. gpt-5.5, glm-5.2) work but are slower and use more tokens; for large papers consider a lighter chat model via --model.
  • Concurrency: modest defaults (--qps 10 --pool-max-workers 30 for the OpenAI engine; --qps 4 --pool-max-workers 8 for claudecode since each segment is a subprocess). Increase for faster translation if the gateway allows it.

When something goes wrong

  • command not found: pdf2zh_next after install — the uv tool bin dir isn't on PATH. The scripts add ~/.local/bin to PATH themselves, but if the user runs pdf2zh_next directly in their own shell, they need export PATH="$HOME/.local/bin:$PATH" (Linux/macOS).
  • First translation hangs on "loading assets" / downloading — normal one-time model download. Wait it out.
  • 429 / rate-limit errors — lower --qps and --pool-max-workers.
  • Gateway returns errors for the OpenAI engine — the detected base_url may only expose the responses API, not chat-completions. Run with --engine siliconflowfree to bypass, or point --base-url at a chat-completions endpoint.
  • Out-of-memory / very large PDFs — use --pages to translate in chunks, or --max-pages-per-part 50.

For the full option reference, engine configuration details, translating to other languages, glossaries, and offline/air-gapped usage, read references/advanced.md.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Pdf Translate AI skill do?

Translate English PDF documents (especially academic papers) into Chinese using PDFMathTranslate-next (pdf2zh), producing a monolingual Chinese PDF and a bilingual side-by-side PDF with formulas, figures, and layout preserved. Automatically installs the pdf2zh_next environment via uv and reuses the model/API the user already configured in Codex or Claude Code (any OpenAI-compatible gateway), falling back to the free SiliconFlow service when no key is present. Use this skill whenever the user wants to translate a PDF to Chinese (or another language), translate a paper/论文, produce a bilingual...

Why use Pdf Translate on TypingMind?

Because you install it once and use it with any model. Pdf Translate is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Pdf Translate in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/L27z18328742/pdf-translate/tree/main. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Pdf Translate?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Pdf Translate?

As many as you like. As long as a model supports skills, you can use Pdf Translate with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Pdf Translate AI skill free?

It is published on GitHub by L27z18328742. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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