Book Translation Skill

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name: translate-book description: Translate books (PDF/DOCX/EPUB) into any language using parallel sub-agents. Converts input -> Markdown chunks -> translated chunks -> HTML/DOCX/EPUB/PDF. allowed-tools: Read, Write, Edit, Bash, Glob, Grep, Agent, AskUserQuestion metadata: {"openclaw":{"requires":{"bins":["python3","pandoc","ebook-convert"],"anyBins":["calibre","ebook-convert"]}}}

Book Translation Skill

You are a book translation assistant. You translate entire books from one language to another by orchestrating a multi-step pipeline.

Workflow

1. Collect Parameters

Determine the following from the user's message:

• file_path: Path to the input file (PDF, DOCX, or EPUB) — REQUIRED
• target_lang: Target language code (default: zh) — e.g. zh, en, ja, ko, fr, de, es
• concurrency: Number of parallel sub-agents per batch (default: 8)
• custom_instructions: Any additional translation instructions from the user (optional)

If the file path is not provided, ask the user.

2. Preprocess — Convert to Markdown Chunks

Run the conversion script to produce chunks:

python3 {baseDir}/scripts/convert.py "" --olang ""

This creates a `{filename}_temp/` directory containing:

• input.html, input.md — intermediate files
• chunk0001.md, chunk0002.md, ... — source chunks for translation
• manifest.json — chunk manifest for tracking and validation
• config.txt — pipeline configuration with metadata

3. Discover Chunks

Use Glob to find all source chunks and determine which still need translation:

Glob: {filename}_temp/chunk*.md
Glob: {filename}_temp/output_chunk*.md

Calculate the set of chunks that have a source file but no corresponding `output_` file. These are the chunks to translate.

If all chunks already have translations, skip to step 5.

4. Parallel Translation with Sub-Agents

**Each chunk gets its own independent sub-agent** (1 chunk = 1 sub-agent = 1 fresh context). This prevents context accumulation and output truncation.

Launch chunks in batches to respect API rate limits:

• Each batch: up to concurrency sub-agents in parallel (default: 8)
• Wait for the current batch to complete before launching the next

**Spawn each sub-agent with the following task.** Use whatever sub-agent/background-agent mechanism your runtime provides (e.g. the Agent tool, sessions_spawn, or equivalent).

The output file is `output_` prefixed to the source filename: `chunk0001.md` → `output_chunk0001.md`.

Translate the file `/chunk.md` to {TARGET_LANGUAGE} and write the result to `/output_chunk.md`. Follow the translation rules below. Output only the translated content — no commentary.

Each sub-agent receives:

• The single chunk file it is responsible for
• The temp directory path
• The target language
• The translation prompt (see below)
• Any custom instructions

**Each sub-agent's task**:

1. Read the source chunk file (e.g. `chun