Qt Translation Assistant Skill
Iron Laws
- Never modify original TS files without backup - Always preserve original content
- Validate AI translation quality - Verify translations are accurate and contextually appropriate
- Maintain translation consistency - Use consistent terminology across all translations
- Respect file encoding - Preserve UTF-8 encoding and special characters
- Minimal changes principle - Only modify translation content, preserve XML structure
Red Flags
- User requests translation of non-TS files
- User asks to translate without proper AI configuration
- Requests to overwrite existing translations without verification
- Asks to translate to unsupported language codes
Rationalization Table
| Excuse | Response |
|---|---|
| "Just translate everything quickly" | Quality matters in localization - proper AI configuration and validation required |
| "We don't need consistent terminology" | Inconsistent translations hurt user experience - consistency is critical |
| "Original files don't need backup" | Always preserve originals - translation errors can corrupt content |
| "Rewrite the whole file" | Only translation text should change - git diff will show other modifications |
Quick Reference
Core Commands
# Translate entire directory of TS files
python translate.py /path/to/ts/files/
# Translate specific file
python translate.py /path/to/file.ts
# With custom batch size and workers
python translate.py /path/to/ts/files/ --batch-size 30 --max-workers 3
# Create configuration file
python translate.py --create-configConfiguration
{
"api_url": "http://localhost:8080/v1/chat/completions",
"api_key": "sk-uos-12345",
"model": "qwen3-coder-flash",
"temperature": 0.3
}Common Mistakes & Fixes
Mistake: AI provider not configured properly
Fix: Create qt_translation_config.json with valid API credentials using --create-config
Mistake: Large files causing API timeouts
Fix: Adjust --batch-size parameter (try 20-50) and --max-workers (try 2-5)
Mistake: Language codes not detected correctly
Fix: Ensure TS files follow standard naming convention (e.g., project_zh_CN.ts, project_de.ts)
Mistake: Translation quality issues
Fix: Adjust model selection and temperature settings in configuration file
Mistake: Git diff shows many unnecessary changes
Fix: The tool only modifies translation content - any other changes indicate a bug that needs fixing
Architecture
This skill uses a parallel processing architecture:
- TranslationWorker: Handles AI API calls with automatic retry and exponential backoff
- QtTranslationAssistant: Main orchestrator with parallel batch processing
- ThreadPoolExecutor: Manages concurrent translation workers (default 3)
Performance improvements over subagent architecture:
- Direct API calls without subprocess overhead (~5-10x faster)
- Larger batch sizes (default 30 vs previous 10)
- Parallel workers (3 concurrent API calls vs sequential)
- Error isolation (single batch failure doesn't affect others)
Key Features
- Smart parsing of TS files to identify incomplete translations
- Parallel batch processing with ThreadPoolExecutor
- Support for multiple AI providers (OpenAI, Anthropic, DeepSeek, local servers)
- Configurable batch size and worker count
- Automatic retries with exponential backoff
- Git diff-friendly modifications (only changes translation content)