Generate four-option vocabulary questions from vocabulary.json and export to CSV.
npx skills add https://github.com/Mu0510/retento --skill question-generator
Please help me install this Agent Skill. Skill: question-generator Source: https://github.com/Mu0510/retento/tree/main/.claude/skills/question-generator Command: npx skills add https://github.com/Mu0510/retento --skill question-generator
This Skill automates the creation of high-quality four-choice questions for Retento's vocabulary, reading from data/vocabulary.json and exporting a CSV-ready dataset, saving hours of manual quiz design.
Use the Retento Question Generator to create 4-option questions for the words in data/vocabulary.json, and export to data/questions-bank.csv.
High-intent search queries and answers about installing and using this skill.
Auto-generate vocabulary quiz questions by reading word data from vocabulary.json and applying generation rules to create four-option multiple-choice items with natural English sentences, Japanese translations, plausible distractors, and explanations. The Skill outputs results in CSV format ready for database import.
Yes. This Skill automates quiz creation for language learning by generating high-quality four-choice questions with contextual sentences, accurate translations, and feedback—eliminating hours of manual question authoring while maintaining consistency across large question banks.
The CSV output includes word, sentence_en, sentence_ja, choices, and feedback fields. This schema matches Retento's database structure for seamless import and supports embedding-based retrieval without additional transformation.
The Skill applies specified generation rules to craft plausible distractors that mirror correct-answer difficulty and generates rich feedback explaining why each option is correct or incorrect, improving learner comprehension in language-learning contexts.
This Skill handles large-scale vocabulary quiz creation—typical use cases involve generating 1,000+ consistent, high-quality questions from a vocabulary dataset, making it suitable for production language-learning applications requiring bulk quiz content.
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