alter123-zz/habit-tracker
skills/habit-tracker/SKILL.md
习惯追踪和问责教练。每日主动签到，追踪习惯连续天数，自适应激励。Keywords: 习惯, 打卡, 自律, habit tracker, accountability.
$ install --global
skillsauthnpx skillsauth add alter123-zz/RaccoonClaw habit-trackerInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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SKILL.md
- name:
- habit-tracker
- description:
- 习惯追踪和问责教练。每日主动签到，追踪习惯连续天数，自适应激励。Keywords: 习惯, 打卡, 自律, habit tracker, accountability.
习惯打卡教练 — 每日主动签到追踪习惯连续天数
概述
每日主动签到追踪习惯连续天数。适用于早起打卡、读书打卡、运动打卡等习惯养成场景。
触发关键词: 习惯, 打卡, 自律, habit tracker, accountability
前置依赖
pip install pandas requests
核心能力
能力1：习惯打卡系统——支持每日/每周/自定义频率
习惯打卡系统——支持每日/每周/自定义频率
能力2：连续天数统计和习惯养成曲线
连续天数统计和习惯养成曲线
能力3：习惯关联分析——发现哪些习惯互相影响
习惯关联分析——发现哪些习惯互相影响
命令列表
| 命令 | 说明 | 用法 |
|------|------|------|
| create | 创建习惯 | python3 scripts/habit_tracker_tool.py create [参数] |
| check | 打卡 | python3 scripts/habit_tracker_tool.py check [参数] |
| stats | 查看统计 | python3 scripts/habit_tracker_tool.py stats [参数] |
使用流程
场景 1
创建习惯：早起6点/阅读30分/运动1小时
执行：
python3 scripts/habit_tracker_tool.py create '早起6点' '阅读30分' '运动1小时'
场景 2
打卡：今天完成了阅读
执行：
python3 scripts/habit_tracker_tool.py check --habit 阅读
场景 3
查看习惯完成统计
执行：
python3 scripts/habit_tracker_tool.py stats --period month
输出格式
# 📊 习惯打卡教练报告
**生成时间**: YYYY-MM-DD HH:MM
## 核心发现
1. [关键发现1]
2. [关键发现2]
3. [关键发现3]
## 数据概览
| 指标 | 数值 | 趋势 | 评级 |
|------|------|------|------|
| 指标A | XXX | ↑ | ⭐⭐⭐⭐ |
| 指标B | YYY | → | ⭐⭐⭐ |
## 详细分析
[基于实际数据的多维度分析内容]
## 行动建议
| 优先级 | 建议 | 预期效果 |
|--------|------|----------|
| 🔴 高 | [具体建议] | [量化预期] |
| 🟡 中 | [具体建议] | [量化预期] |
| 🟢 低 | [具体建议] | [量化预期] |
参考资料
原有链接
- James Clear习惯追踪法，原子习惯策略
- 习惯追踪教练Agent完整用例
- Habitica API，游戏化习惯养成
HackerNews
- HackerNews: AI习惯追踪工具和打卡机制
- Reddit r/theXeffect: theXeffect社区AI相关讨论
微信公众号
- 微信公众号: AI习惯教练——从打卡到养成好习惯
小红书
- 小红书: 打卡100天——AI习惯教练帮我坚持
注意事项
- 所有分析基于脚本获取的实际数据，不编造数据
- 数据缺失字段标注"数据不可用"而非猜测
- 建议结合人工判断使用，AI分析仅供参考
- 首次使用请先安装Python依赖：
pip install pandas requests
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