Epub Translator

EPUB Translation Skill

Translate EPUB files between any language pair with optimized support for Japanese and English to Korean.

When to Use This Skill

Use this skill when:

• User wants to translate an EPUB ebook to another language
• User mentions translating Japanese/English/Chinese novels or books
• User has multiple EPUB files to translate in batch
• User needs to preserve EPUB formatting and structure during translation

Usage

/epub-translator <epub_path> [options]

Arguments

• <epub_path>: EPUB file or directory containing EPUBs

Options

Language Codes

ja (Japanese), en (English), ko (Korean), zh (Chinese), es (Spanish), fr (French), de (German), ru (Russian), ar (Arabic), or any ISO 639-1 code.

Examples

# Japanese novel to Korean (default)
/epub-translator "/books/novel.epub"

# English to Korean
/epub-translator "/books/english.epub" --source-lang en

# Japanese to English
/epub-translator "/books/jp_novel.epub" --source-lang ja --target-lang en

# High-quality translation using the runtime's stronger model
/epub-translator "/books/important.epub" --high-quality

# Batch with larger split threshold (less splitting)
/epub-translator "/books/" --split-threshold 50 --parallel 10

# More aggressive splitting for slower connections
/epub-translator "/books/large.epub" --split-threshold 20 --split-parts 6

# English to Japanese with vertical writing (우종서/縦書き)
/epub-translator "/books/novel.epub" --source-lang en --target-lang ja --vertical

# Korean to Chinese with vertical writing
/epub-translator "/books/korean.epub" --source-lang ko --target-lang zh --vertical

Architecture

graph TB
    O["ORCHESTRATOR<br/>• Analyzes EPUBs and creates task manifest<br/>• Dispatches translation work using available agent/runtime features<br/>• Collects translated section files<br/>• Validates translation quality<br/>• Handles retries and error recovery"]
    T1["Translator<br/>Agent 1"]
    T2["Translator<br/>Agent 2"]
    TN["Translator<br/>Agent N"]

    O --> T1
    O --> T2
    O --> TN

Execution Model: Translate independent files or sections in parallel when the active runtime supports parallel agents. If parallel dispatch is unavailable, process the manifest sequentially with the same prompts and filesystem outputs.

Model Selection

Default (no flags)

With --high-quality

Automatic Upgrade

• If quality score < 70: Re-translate flagged files with a stronger model
• If translation fails: Retry with upgraded model

Execution Workflow

Phase 1: Analysis

1. Create work directory:

   WORK_DIR="/tmp/epub_translate_$(date +%s)"
   mkdir -p "$WORK_DIR"/{extracted,sections,translated,status,logs}
   

2. Analyze EPUBs (with configurable split threshold):

   python3 scripts/analyze_epub.py \
     --epub "{EPUB_PATH}" \
     --work-dir "$WORK_DIR" \
     --source-lang "{SOURCE_LANG}" \
     --target-lang "{TARGET_LANG}" \
     --split-threshold 30 \
     --split-parts 4
   

3. Review $WORK_DIR/manifest.json for task count.

Phase 2: Translation

1. Select translator prompt from references/:

   • Japanese: translator_ja.md
   • English: translator_en.md
   • Other: translator_generic.md

2. Dispatch translation work in batches:

   • Use parallel agents if the runtime supports them
   • Otherwise translate each manifest entry sequentially
   • Process in batches of --parallel count when parallelism is available
   • Require each task to write its translated output file and status file

3. Batch execution pattern:

   For each batch of N tasks:
     - Dispatch N translation jobs when parallelism is available
     - Confirm each expected output file exists
     - Track completed/failed tasks
     - Proceed to next batch
   

4. Retry failed tasks (max 2 attempts, use a stronger model if persistent)

Phase 3: Finalization

1. Merge split files:

   python3 scripts/merge_xhtml.py --work-dir "$WORK_DIR" --manifest manifest.json
   

2. Translate metadata and navigation (LLM-based):

   • Run a metadata translation pass using translator_metadata.md
   • Translate: toc.ncx, nav.xhtml, content.opf (title, author, description)
   • Translate: cover.xhtml, titlepage.xhtml (if present)
   • Ensure TOC entries match translated chapter headings

3. Apply layout conversion (CRITICAL - must be done before packaging):

   Determine conversion type based on target language and --vertical option:

   Target Language	--vertical	Result
   ko, en, etc.	(ignored)	horizontal-tb, ltr
   ja, zh	false (default)	horizontal-tb, ltr
   ja, zh	true	vertical-rl, rtl (우종서/縦書き)
   ar, he, fa	(ignored)	horizontal-tb, rtl

   A. Horizontal output (default for all languages):

   TRANSLATED_DIR="$WORK_DIR/translated/{VOLUME_ID}"
   
   # Convert CSS files: vertical-rl → horizontal-tb
   find "$TRANSLATED_DIR" -name "*.css" -exec sed -i '' \
       -e 's/writing-mode:[[:space:]]*vertical-rl/writing-mode: horizontal-tb/g' \
       -e 's/-webkit-writing-mode:[[:space:]]*vertical-rl/-webkit-writing-mode: horizontal-tb/g' \
       -e 's/-epub-writing-mode:[[:space:]]*vertical-rl/-epub-writing-mode: horizontal-tb/g' \
       {} \;
   
   # Convert content.opf: page direction and writing mode
   find "$TRANSLATED_DIR" -name "content.opf" -exec sed -i '' \
       -e 's/page-progression-direction="rtl"/page-progression-direction="ltr"/g' \
       -e 's/primary-writing-mode" content="vertical-rl"/primary-writing-mode" content="horizontal-tb"/g' \
       {} \;
   
   # Convert XHTML inline styles if present
   find "$TRANSLATED_DIR" -name "*.xhtml" -exec sed -i '' \
       -e 's/writing-mode:[[:space:]]*vertical-rl/writing-mode: horizontal-tb/g' \
       {} \;
   

   B. Vertical output (only when --vertical AND target is ja/zh):

   TRANSLATED_DIR="$WORK_DIR/translated/{VOLUME_ID}"
   
   # Convert CSS files: horizontal-tb → vertical-rl
   find "$TRANSLATED_DIR" -name "*.css" -exec sed -i '' \
       -e 's/writing-mode:[[:space:]]*horizontal-tb/writing-mode: vertical-rl/g' \
       -e 's/-webkit-writing-mode:[[:space:]]*horizontal-tb/-webkit-writing-mode: vertical-rl/g' \
       -e 's/-epub-writing-mode:[[:space:]]*horizontal-tb/-epub-writing-mode: vertical-rl/g' \
       {} \;
   
   # Convert content.opf: page direction and writing mode for vertical
   find "$TRANSLATED_DIR" -name "content.opf" -exec sed -i '' \
       -e 's/page-progression-direction="ltr"/page-progression-direction="rtl"/g' \
       -e 's/primary-writing-mode" content="horizontal-tb"/primary-writing-mode" content="vertical-rl"/g' \
       {} \;
   
   # Convert XHTML inline styles if present
   find "$TRANSLATED_DIR" -name "*.xhtml" -exec sed -i '' \
       -e 's/writing-mode:[[:space:]]*horizontal-tb/writing-mode: vertical-rl/g' \
       {} \;
   

   C. RTL output (for ar/he/fa targets):

   # Convert page direction
   sed -i '' 's/page-progression-direction="ltr"/page-progression-direction="rtl"/g' "$TRANSLATED_DIR"/content.opf
   
   # Convert CSS direction
   find "$TRANSLATED_DIR" -name "*.css" -exec sed -i '' \
       -e 's/direction:[[:space:]]*ltr/direction: rtl/g' \
       {} \;
   

   Note: If source is already vertical and --vertical is set, skip CSS conversion (keep existing vertical layout).

   See references/layout_conversion.md for complete conversion patterns.

4. Verify source text removed:

   python3 scripts/verify.py --work-dir "$WORK_DIR" --source-lang "{SOURCE_LANG}"
   

Phase 4: Quality Validation (LLM-Based)

1. Extract text for validation (token-efficient format):

   python3 scripts/extract_for_validation.py \
     --dir "$WORK_DIR/translated" \
     --output-dir "$WORK_DIR/validation" \
     --max-tokens 8000
   

2. Select validator prompt from references/:

   • Korean target: validator_ko.md (extends validator_generic.md)
   • Other targets: validator_generic.md

3. Spawn validation Task agents in foreground mode (batched):

   • Read $WORK_DIR/validation/validation_manifest.json
   • For each chunk, spawn a validator agent with:
     • model: "haiku" (sufficient for validation)
   • CRITICAL: Multiple Tasks in single message for parallel execution
   • Process in batches, collect results directly

4. Aggregate results:

   • Collect validation results from agent responses
   • Calculate average quality score
   • Identify files flagged for re-translation

5. If average score < 70: Re-translate flagged files with model: "opus"

Phase 5: Packaging

1. Package EPUB:

   bash scripts/package_epub.sh "$WORK_DIR" "{OUTPUT_DIR}"
   

2. Generate final report with quality metrics

File Splitting Configuration

Conservative defaults prevent context overflow in translation agents:

Tuning Guidelines

• Slow connection / Timeouts: Lower threshold (20 KB), more parts (6)
• Fast connection / Large context: Higher threshold (50 KB), fewer parts (3)
• Very large files (100KB+): Will be split into more parts automatically

Quality Validation (LLM-Based)

Translation quality is validated by an LLM-based review pass, not regex patterns. This provides:

• Context-aware naturalness assessment
• Understanding of literary style and tone
• Detection of subtle translation issues

Validator Instructions

Korean-Specific Checks

• Translationese (번역투): ~하는 것이다, ~라고 하는, etc.
• Pronoun overuse: Excessive 그녀는, 그는
• Particle chains: Awkward 의의의 patterns
• Honorific consistency: Speech level matching

Quality Score

• 90-100: Excellent - reads naturally
• 75-89: Good - minor issues
• 60-74: Acceptable - review recommended
• <60: Poor - re-translation needed

Validation Workflow

1. Text extracted in token-efficient format
2. Chunked for parallel validation (8000 tokens each)
3. LLM validators spawned in foreground batches
4. Results collected directly from agent responses
5. Results aggregated into final report

Language-Specific Processing

Source Language Handling

Layout Conversion (Target-Based)

Key Principle: All languages default to horizontal LTR (except RTL languages).

Note: --vertical option is only valid for Japanese (ja) and Chinese (zh) targets. It will be ignored for other languages.

See references/layout_conversion.md for complete conversion scripts.

Custom Dictionary (Optional)

The translator works without external dictionary files. It naturally translates based on context.

Use custom dictionaries ONLY for:

• Proper nouns: names, places, organizations, brands
• Document-specific terms: proprietary terms unique to this document

Do NOT add common words - let the translator handle them naturally.

Creating a Custom Dictionary

See assets/template.json for format:

{
  "proper_nouns": { "names": { "田中太郎": "Tanaka Taro" } },
  "domain_terms": { "ProprietaryTech": "고유 기술명" }
}

Academic/Technical Template

For academic or technical documents, use assets/template_academic.json.

Work Directory Structure

$WORK_DIR/
├── manifest.json           # Task manifest
├── extracted/              # Extracted EPUB contents
├── sections/               # Split large files
├── translated/             # Translated files
├── validation/             # Validation input/output files
│   ├── validation_manifest.json
│   ├── validate_001_input.txt
│   ├── validate_001_result.json
│   └── ...
├── status/                 # Task status files
└── logs/                   # Log files

Status Codes

Error Handling

File Reference