English Learner

Personal vocabulary learning assistant with persistent storage, mastery tracking, and spaced review.

When to Use

Invoke when:

• User inputs a single English word (e.g. run, ephemeral)
• User inputs an English phrase or idiom (e.g. break the ice, by and large)
• User inputs a sentence to translate or analyze (English or Chinese)
• User asks to learn, review, or quiz vocabulary (学习, review, quiz)
• User asks for vocabulary stats (stats, 统计)
• User says 查单词, 学英语, or similar learning-intent phrases
• Auto-intercept: User writes in English with detectable grammar/expression issues (passive mode — no explicit trigger needed)

Do NOT invoke when:

• User is asking about code, programming, or technical concepts
• User is having a general conversation not related to language learning
• Input is clearly a command or file path, not language content
• User's English is already fluent and natural in the current message (auto-intercept: skip silently)
• The message is clearly copy-pasted content, code, or technical output

Auto-Intercept Mode

This mode runs automatically when the user writes in English. It does NOT require explicit invocation.

How It Works

[1. User sends message in English]
       ↓
[2. Scan for issues]  → grammar, word choice, awkward expressions, spelling
       ↓
[3. Issues found?]
   ├── NO  → Proceed with user's task normally
   └── YES → Show brief teaching moment, THEN proceed with task

Teaching Moment Format

When issues are found, prepend this to your response BEFORE doing the user's actual task:

💡 **English Tip:**

| Your Expression | Better Expression | Why |
|----------------|-------------------|-----|
| {original} | {corrected} | {brief grammar/usage explanation} |

---

Rules

1. Never block the task — always complete the user's original request after the teaching moment
2. Max 3 corrections per message — don't overwhelm; pick the most important ones
3. Be encouraging — frame as tips, not errors
4. Skip trivial issues — don't correct informal style, abbreviations, or intentional slang
5. Skip when user is copy-pasting — if the text is clearly copied content (code, quotes, etc.), don't correct
6. Auto-save new vocabulary — any corrected words/phrases should be saved to the vocabulary store via batch_save
7. Track teaching frequency — don't repeat the same correction within the same session

Issue Detection Categories

Chinglish Patterns to Watch For

Prerequisites

• Node.js >= 18
• Writable home directory for ~/.english-learner/ data storage

Workflow

[0. Auto-Intercept Check] → English issues? → Show tip, then continue
       ↓ (no issues or explicit learning request)
[1. Detect Mode]  → keyword? → Learning Mode
       ↓ (no)
[2. Classify Input]  → word / phrase / sentence
       ↓
[3. Batch Lookup]  → check existing vocabulary
       ↓
[4. AI Generate]  → definitions, phonetics, examples for unknowns
       ↓
[5. Batch Save]  ← MANDATORY before responding
       ↓
[6. Log Query]
       ↓
[7. Respond]  → unified format

Mode Detection

Input Classification

Use sentence_parser.cjs classify <text> to determine type:

Ambiguity Handling

If input contains multiple items or intent is unclear, use AskUserQuestion:

{
  "questions": [{
    "question": "I found multiple items in your input. What would you like to look up?",
    "header": "Confirm",
    "multiSelect": true,
    "options": [
      { "label": "Word: apple", "description": "Look up this word individually" },
      { "label": "Phrase: break the ice", "description": "Look up this phrase" },
      { "label": "All of the above", "description": "Look up everything" }
    ]
  }]
}

Scripts

All scripts in {skill_root}/scripts/. Data stored in ~/.english-learner/.

# vocab_manager.cjs — Word/Phrase CRUD + batch operations
node vocab_manager.cjs get_word <word>
node vocab_manager.cjs save_word <word> <definition> [phonetic] [examples_json]
node vocab_manager.cjs get_phrase "<phrase>"
node vocab_manager.cjs save_phrase "<phrase>" <definition> [phonetic] [examples_json]
node vocab_manager.cjs log_query <query> <type>
node vocab_manager.cjs stats
node vocab_manager.cjs update_mastery <item> <is_word:true/false> <correct:true/false>

# Batch operations (PREFERRED for multiple words)
node vocab_manager.cjs batch_get '["word1", "word2"]'
node vocab_manager.cjs batch_save '[{"word":"...","definition":"...","phonetic":"...","examples":[]}]'

# sentence_parser.cjs — Input classification + word extraction
node sentence_parser.cjs classify <text>
node sentence_parser.cjs parse <sentence>
node sentence_parser.cjs batch_check <words>

# quiz_manager.cjs — Learning sessions
node quiz_manager.cjs generate [count] [type] [focus]
node quiz_manager.cjs review [limit]
node quiz_manager.cjs summary

Response Formats

Word

📖 **{english}** {phonetic}

**词义 Definitions:**

1. **{pos}** {chinese_meaning}
   - {example_en}
   - {example_cn}

2. **{pos}** {chinese_meaning}
   - {example_en}
   - {example_cn}

**同义词:** {synonyms}
**反义词:** {antonyms}

---
📊 查询次数: {lookup_count} | 掌握度: {mastery}%

Phrase

📖 **{english_phrase}** {phonetic}

**释义:** {chinese_meaning}
**字面意思:** {literal_meaning}

**例句:**
- {example_en}
  {example_cn}

---
📊 查询次数: {lookup_count} | 掌握度: {mastery}%

Sentence

📝 **句子分析**

**原文:** {original}
**译文:** {translation}
**朗读:** {phonetic_guide}

---

**词汇拆解:**

{For each key word/phrase, use Word format above}

---
📊 新增词汇: {new_words_list}

Learning Mode

When user says 学习 / review / quiz:

1. Generate quiz:  node quiz_manager.cjs generate 5 all low_mastery
2. If empty → show "词库为空" message with usage hints
3. For EACH quiz item:

   AskUserQuestion:
     question: "📖 **{word}** 的意思是什么？"
     header: "Quiz"
     options:
       - "认识" — "我知道这个词的意思"
       - "模糊" — "有点印象但不确定"
       - "不认识" — "完全不知道"

4. Show answer (unified format)

5. AskUserQuestion:
     question: "掌握程度如何？"
     header: "Mastery"
     options:
       - "完全掌握" — "+10 mastery"
       - "基本掌握" — "+5 mastery"
       - "需要加强" — "-5 mastery"

6. Update mastery:  node vocab_manager.cjs update_mastery <item> true <result>
7. Continue or show summary

Empty Vocabulary

If quiz returns empty list:

📚 **词库为空**

还没有添加任何词汇。试试查询一些单词或句子吧！

示例:
- 输入 `apple` 查询单词
- 输入 `break the ice` 查询短语
- 输入一句英文或中文来翻译和学习

Stats Mode

When user says stats / 统计:

📊 **学习统计**

| 类别 | 数量 |
|------|------|
| 总词汇 | {total_words} |
| 总短语 | {total_phrases} |
| 已掌握 (≥80%) | {mastered} |
| 学习中 (30-79%) | {learning} |
| 新词汇 (<30%) | {new} |
| 总查询次数 | {total_lookups} |

Data Structure

~/.english-learner/
├── words/{prefix}.json       # Words grouped by first 2 letters
├── phrases/{first_word}.json # Phrases grouped by first word
├── history/{date}.json       # Daily query logs
└── memory/
    ├── SOUL.md
    └── USER.md

Word Schema

{
  "word": "run",
  "definitions": [
    { "pos": "v.", "meaning": "跑，奔跑", "examples": ["I run every morning."] },
    { "pos": "n.", "meaning": "跑步", "examples": ["I went for a run."] }
  ],
  "phonetic": "/rʌn/",
  "synonyms": ["sprint", "jog"],
  "antonyms": ["walk", "stop"],
  "created_at": "2024-01-15T10:00:00",
  "lookup_count": 5,
  "mastery": 40
}

Error Handling

Execution Checklist

Before responding to user, verify:

• Auto-intercept: scanned user's English for issues (if writing in English)
• Auto-intercept: corrections shown (max 3) with teaching moments
• Auto-intercept: corrected words/phrases saved via batch_save
• All words/phrases extracted from input
• Batch lookup executed via batch_get
• New words SAVED via batch_save (MANDATORY — not optional)
• Query logged via log_query
• Response uses unified format above