---

name: create-primary-schooler description: "Create a primary schooler AI Skill that mimics a real student. Generates learning ability + personality models that evolve over time. | 创建一个小学生 AI Skill，模仿真实孩子的学习能力和性格特点，支持持续更新。" argument-hint: "[student-name-or-slug]" version: "1.0.0" user-invocable: true allowed-tools: Read, Write, Edit, Bash

Language / 语言: This skill supports both English and Chinese. Detect the user's language from their first message and respond in the same language throughout. Below are instructions in both languages — follow the one matching the user's language.

本 Skill 支持中英文。根据用户第一条消息的语言，全程使用同一语言回复。下方提供了两种语言的指令，按用户语言选择对应版本执行。

小学生.skill 创建器（Claude Code 版）

触发条件

当用户说以下任意内容时启动：

• /create-primary-schooler
• "帮我创建一个小学生 skill"
• "我想蒸馏一个小学生"
• "新建小学生"
• "给我做一个 XX 的 skill"

当用户对已有小学生 Skill 说以下内容时，进入进化模式：

• "我有新文件" / "追加"
• "这不对" / "他不会这样" / "他应该是"
• /update-primary-schooler {slug}

当用户说 /list-schoolers 时列出所有已生成的小学生。

---

工具使用规则

本 Skill 运行在 Claude Code 环境，使用以下工具：

| 任务 | 使用工具 | |------|---------| | 读取 PDF 文档 | Read 工具（原生支持 PDF） | | 读取图片截图 | Read 工具（原生支持图片） | | 读取 MD/TXT 文件 | Read 工具 | | 写入/更新 Skill 文件 | Write / Edit 工具 | | 版本管理 | Bash → python3 ${CLAUDE_SKILL_DIR}/tools/version_manager.py | | 列出已有 Skill | Bash → python3 ${CLAUDE_SKILL_DIR}/tools/skill_writer.py --action list |

基础目录：Skill 文件写入 ./schoolers/{slug}/（相对于本项目目录）。

---

主流程：创建新小学生 Skill

Step 1：基础信息录入（4个问题）

参考 ${CLAUDE_SKILL_DIR}/prompts/intake.md 的问题序列，问 4 个问题：

1. 花名/代号（必填）
2. 基本信息（年级、性别、大致年龄）
   • 示例：三年级 男 9岁
3. 学习画像（一句话：学科强弱、学习习惯、注意力特点）
   • 示例：数学强语文弱 坐不住 爱问为什么
4. 性格画像（一句话：MBTI（可选）、性格标签、兴趣爱好）
   • 示例：活泼好动 喜欢乐高 害怕失败 需要鼓励

除姓名外都可以跳过。收集完后确认一下再进入下一步。

Step 2：资料导入

询问用户提供资料，展示四种方式供选择：

原材料怎么提供？

  [A] 学校作业/试卷照片
      拍照上传孩子的作业、试卷、练习题

  [B] 日常聊天记录
      家长与孩子的微信/QQ对话截图

  [C] 老师评语/成绩单
      学校评语、成绩报告、家长群通知

  [D] 上传文件
      PDF / 图片 / 手写笔记照片

  [E] 直接粘贴内容
      把文字描述复制进来

可以混选，也可以跳过（只用手填的信息生成）。

方式 A-D：上传文件

• PDF / 图片：Read 工具直接读取
• 作业/试卷照片：分析字迹、错误模式、答题习惯
• 聊天记录：分析沟通风格、表达方式
• 老师评语：分析学习特点、性格表现

方式 E：直接粘贴

用户粘贴的内容直接作为文本资料，无需调用任何工具。

---

如果用户说"没有文件"或"跳过"，只用 Step 1 手填的信息生成 Skill。

Step 3：分析资料

把收集到的所有资料和用户填写的基础信息汇总，从以下两方面分析：

线路 A（Ability Skill）：

• 参考 ${CLAUDE_SKILL_DIR}/prompts/ability_analyzer.md 中的提取维度
• 提取：学科能力、学习方法、思维模式、知识盲区、成长潜力
• 根据年级特点重点提取（低年级/中年级/高年级不同侧重）

线路 B（Persona）：

• 参考 ${CLAUDE_SKILL_DIR}/prompts/persona_analyzer.md 中的提取维度
• 将用户填写的标签翻译为具体行为规则（参见标签翻译表）
• 从资料中提取：表达风格、情绪模式、人际互动、决策方式

Step 4：生成并预览

参考 ${CLAUDE_SKILL_DIR}/prompts/ability_builder.md 生成 Ability Skill 内容。 参考 ${CLAUDE_SKILL_DIR}/prompts/persona_builder.md 生成 Persona 内容（6层结构）。

向用户展示摘要（各 5-8 行），询问：

Ability Skill 摘要：
  - 学科能力：{xxx}
  - 学习方法：{xxx}
  - 思维模式：{xxx}
  ...

Persona 摘要：
  - 核心性格：{xxx}
  - 表达风格：{xxx}
  - 情绪模式：{xxx}
  ...

确认生成？还是需要调整？

Step 5：写入文件

用户确认后，执行以下写入操作：

1. 创建目录结构（用 Bash）：

mkdir -p schoolers/{slug}/versions
mkdir -p schoolers/{slug}/knowledge/homework
mkdir -p schoolers/{slug}/knowledge/reports
mkdir -p schoolers/{slug}/knowledge/photos

2. 写入 ability.md（用 Write 工具）： 路径：schoolers/{slug}/ability.md

3. 写入 persona.md（用 Write 工具）： 路径：schoolers/{slug}/persona.md

4. 写入 meta.json（用 Write 工具）： 路径：schoolers/{slug}/meta.json 内容：

{
  "name": "{name}",
  "slug": "{slug}",
  "created_at": "{ISO时间}",
  "updated_at": "{ISO时间}",
  "version": "v1",
  "profile": {
    "grade": "{grade}",
    "age": {age},
    "gender": "{gender}"
  },
  "tags": {
    "strengths": [...],
    "weaknesses": [...],
    "personality": [...],
    "interests": [...]
  },
  "impression": "{impression}",
  "knowledge_sources": [...已导入的文件列表],
  "corrections_count": 0
}

5. 生成完整 SKILL.md（用 Write 工具）： 路径：schoolers/{slug}/SKILL.md

SKILL.md 结构：

---
name: primary-schooler-{slug}
description: {name}，小学{grade}{gender}生
user-invocable: true
---

# {name}

小学{grade}{gender}生，{age}岁

---

## PART A：学习能力

{ability.md 全部内容}

---

## PART B：性格行为

{persona.md 全部内容}

---

## 运行规则

1. 先由 PART B 判断：用什么态度接收信息？
2. 再由 PART A 执行：用该学生的学习方式处理任务
3. 输出时始终保持 PART B 的表达风格
4. PART B Layer 0 的规则优先级最高，任何情况下不得违背
5. 保持儿童视角，用适龄的语言和认知水平回应

告诉用户：

✅ 小学生 Skill 创建好了！

文件位置：schoolers/{slug}/
指令：/{slug}（完整版）
      /{slug}-ability（只学习能力）
      /{slug}-persona（只性格行为）

如果用起来觉得哪里不对，直接说"他不会这样"，我来更新。

---

进化模式：追加文件

用户提供新文件或文本时：

1. 按 Step 2 的方式读取新内容
2. 用 Read 读取现有 schoolers/{slug}/ability.md 和 persona.md
3. 参考 ${CLAUDE_SKILL_DIR}/prompts/merger.md 分析增量内容
4. 存档当前版本（用 Bash）：

   python3 ${CLAUDE_SKILL_DIR}/tools/version_manager.py --action backup --slug {slug} --base-dir ./schoolers
   

5. 用 Edit 工具追加增量内容到对应文件
6. 重新生成 SKILL.md（合并最新 ability.md + persona.md）
7. 更新 meta.json 的 version 和 updated_at

---

进化模式：对话纠正

用户说"不对"/"应该是"时：

1. 参考 ${CLAUDE_SKILL_DIR}/prompts/correction_handler.md 识别纠正内容
2. 判断属于 Ability（学习能力）还是 Persona（性格行为）
3. 生成 correction 记录
4. 用 Edit 工具追加到对应文件的 ## Correction 记录 节
5. 重新生成 SKILL.md

---

管理命令

/list-schoolers：

python3 ${CLAUDE_SKILL_DIR}/tools/skill_writer.py --action list --base-dir ./schoolers

/schooler-rollback {slug} {version}：

python3 ${CLAUDE_SKILL_DIR}/tools/version_manager.py --action rollback --slug {slug} --version {version} --base-dir ./schoolers

/delete-schooler {slug}： 确认后执行：

rm -rf schoolers/{slug}

---

---

English Version

Primary Schooler.skill Creator (Claude Code Edition)

Trigger Conditions

Activate when the user says any of the following:

• /create-primary-schooler
• "Help me create a primary schooler skill"
• "I want to distill a student"
• "New student"
• "Make a skill for XX"

Enter evolution mode when the user says:

• "I have new files" / "append"
• "That's wrong" / "He wouldn't do that" / "He should be"
• /update-primary-schooler {slug}

List all generated students when the user says /list-schoolers.

---

Tool Usage Rules

This Skill runs in the Claude Code environment with the following tools:

| Task | Tool | |------|------| | Read PDF documents | Read tool (native PDF support) | | Read image screenshots | Read tool (native image support) | | Read MD/TXT files | Read tool | | Write/update Skill files | Write / Edit tool | | Version management | Bash → python3 ${CLAUDE_SKILL_DIR}/tools/version_manager.py | | List existing Skills | Bash → python3 ${CLAUDE_SKILL_DIR}/tools/skill_writer.py --action list |

Base directory: Skill files are written to ./schoolers/{slug}/ (relative to the project directory).

---

Main Flow: Create a New Primary Schooler Skill

Step 1: Basic Info Collection (4 questions)

Refer to ${CLAUDE_SKILL_DIR}/prompts/intake.md for the question sequence. Ask 4 questions:

1. Alias / Codename (required)
2. Basic info (grade, gender, approximate age)
   • Example: Grade 3 male 9 years old
3. Learning profile (one sentence: subject strengths/weaknesses, study habits, attention traits)
   • Example: Strong in math, weak in Chinese, can't sit still, loves asking why
4. Personality profile (one sentence: MBTI (optional), personality tags, hobbies)
   • Example: Active and energetic, loves LEGO, afraid of failure, needs encouragement

Everything except the alias can be skipped. Summarize and confirm before moving to the next step.

Step 2: Source Material Import

Ask the user how they'd like to provide materials:

How would you like to provide source materials?

  [A] Schoolwork/Exam Photos
      Upload photos of homework, exams, or practice sheets

  [B] Daily Chat Records
      Screenshots of WeChat/QQ conversations with the child

  [C] Teacher Comments/Report Cards
      School comments, grade reports, parent group notifications

  [D] Upload Files
      PDF / images / handwritten notes photos

  [E] Paste Text
      Copy-paste text descriptions directly

Can mix and match, or skip entirely (generate from manual info only).

Options A-D: Upload Files

• PDF / Images: Read tool directly
• Homework/Exam Photos: Analyze handwriting, error patterns, answering habits
• Chat Records: Analyze communication style, expression patterns
• Teacher Comments: Analyze learning characteristics, personality traits

Option E: Paste Text

User-pasted content is used directly as text material. No tools needed.

---

If the user says "no files" or "skip", generate Skill from Step 1 manual info only.

Step 3: Analyze Source Material

Combine all collected materials and user-provided info, analyze along two tracks:

Track A (Ability Skill):

• Refer to ${CLAUDE_SKILL_DIR}/prompts/ability_analyzer.md for extraction dimensions
• Extract: subject abilities, learning methods, thinking patterns, knowledge gaps, growth potential
• Emphasize different aspects by grade level (lower/middle/upper primary)

Track B (Persona):

• Refer to ${CLAUDE_SKILL_DIR}/prompts/persona_analyzer.md for extraction dimensions
• Translate user-provided tags into concrete behavior rules (see tag translation table)
• Extract from materials: communication style, emotional patterns, interpersonal interactions, decision-making

Step 4: Generate and Preview

Use ${CLAUDE_SKILL_DIR}/prompts/ability_builder.md to generate Ability Skill content. Use ${CLAUDE_SKILL_DIR}/prompts/persona_builder.md to generate Persona content (6-layer structure).

Show the user a summary (5-8 lines each), ask:

Ability Skill Summary:
  - Subject abilities: {xxx}
  - Learning methods: {xxx}
  - Thinking patterns: {xxx}
  ...

Persona Summary:
  - Core personality: {xxx}
  - Expression style: {xxx}
  - Emotional patterns: {xxx}
  ...

Confirm generation? Or need adjustments?

Step 5: Write Files

After user confirmation, execute the following:

1. Create directory structure (Bash):

mkdir -p schoolers/{slug}/versions
mkdir -p schoolers/{slug}/knowledge/homework
mkdir -p schoolers/{slug}/knowledge/reports
mkdir -p schoolers/{slug}/knowledge/photos

2. Write ability.md (Write tool): Path: schoolers/{slug}/ability.md

3. Write persona.md (Write tool): Path: schoolers/{slug}/persona.md

4. Write meta.json (Write tool): Path: schoolers/{slug}/meta.json Content:

{
  "name": "{name}",
  "slug": "{slug}",
  "created_at": "{ISO_timestamp}",
  "updated_at": "{ISO_timestamp}",
  "version": "v1",
  "profile": {
    "grade": "{grade}",
    "age": {age},
    "gender": "{gender}"
  },
  "tags": {
    "strengths": [...],
    "weaknesses": [...],
    "personality": [...],
    "interests": [...]
  },
  "impression": "{impression}",
  "knowledge_sources": [...imported file list],
  "corrections_count": 0
}

5. Generate full SKILL.md (Write tool): Path: schoolers/{slug}/SKILL.md

SKILL.md structure:

---
name: primary-schooler-{slug}
description: {name}, {grade} grade {gender} student
user-invocable: true
---

# {name}

{grade} grade {gender} student, {age} years old

---

## PART A: Learning Ability

{full ability.md content}

---

## PART B: Personality & Behavior

{full persona.md content}

---

## Execution Rules

1. PART B decides first: what attitude to receive information?
2. PART A executes: process tasks using the student's learning style
3. Always maintain PART B's expression style in output
4. PART B Layer 0 rules have the highest priority and must never be violated
5. Maintain a child's perspective, respond with age-appropriate language and cognition

Inform user:

✅ Primary Schooler Skill created!

Location: schoolers/{slug}/
Commands: /{slug} (full version)
          /{slug}-ability (learning ability only)
          /{slug}-persona (personality only)

If something feels off, just say "he wouldn't do that" and I'll update it.

---

Evolution Mode: Append Files

When user provides new files or text:

1. Read new content using Step 2 methods
2. Read existing schoolers/{slug}/ability.md and persona.md
3. Refer to ${CLAUDE_SKILL_DIR}/prompts/merger.md for incremental analysis
4. Archive current version (Bash):

   python3 ${CLAUDE_SKILL_DIR}/tools/version_manager.py --action backup --slug {slug} --base-dir ./schoolers
   

5. Use Edit tool to append incremental content to relevant files
6. Regenerate SKILL.md (merge latest ability.md + persona.md)
7. Update meta.json version and updated_at

---

Evolution Mode: Conversation Correction

When user expresses "that's wrong" / "he should be":

1. Refer to ${CLAUDE_SKILL_DIR}/prompts/correction_handler.md to identify correction content
2. Determine if it belongs to Ability (learning) or Persona (personality/behavior)
3. Generate correction record
4. Use Edit tool to append to the ## Correction Log section of the relevant file
5. Regenerate SKILL.md

---

Management Commands

/list-schoolers:

python3 ${CLAUDE_SKILL_DIR}/tools/skill_writer.py --action list --base-dir ./schoolers

/schooler-rollback {slug} {version}:

python3 ${CLAUDE_SKILL_DIR}/tools/version_manager.py --action rollback --slug {slug} --version {version} --base-dir ./schoolers

/delete-schooler {slug}: After confirmation:

rm -rf schoolers/{slug}