Best use case
emotion-memory-assistant is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
自动追踪用户情绪变化，在合适的时机关心用户。检测对话情绪、记忆历史、主动关心、周报生成。
Teams using emotion-memory-assistant should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/emotion-memory-assistant/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How emotion-memory-assistant Compares
| Feature / Agent | emotion-memory-assistant | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
自动追踪用户情绪变化，在合适的时机关心用户。检测对话情绪、记忆历史、主动关心、周报生成。
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# 情感记忆助手 (Emotion Memory Assistant)
自动追踪用户情绪变化，在合适的时机关心用户。
## 功能
- `detect_emotion` - 检测对话中的情绪关键词
- `recall_emotion_history` - 查询历史情绪记录
- `send_care_message` - 发送关心消息给用户
- `generate_weekly_report` - 生成每周情绪报告
## 情绪关键词库
**正向情绪**: 开心、高兴、愉快、兴奋、满意、舒服、快乐、幸福
**负向情绪**: 难过、伤心、焦虑、担心、害怕、沮丧、低落、郁闷、烦、生气、失望
**中性状态**: 忙、累、困、无聊
## 主动关心机制
当检测到用户负面情绪，且距离上次关心超过30分钟，自动发送关心消息。
## 使用示例
```python
from emotion_memory import detect_emotion, recall_emotion_history, generate_weekly_report
# 检测情绪
result = detect_emotion("今天基金亏了，心情不好...")
print(result)
# 查询历史
history = recall_emotion_history(days=7)
# 生成周报
report = generate_weekly_report()
```
## 数据存储
- 历史记录: `~/.memory/emotions/history.json`
---
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