Overview
- Skill Key
- eightroad/channel-activity-yanyue
- Author
- eightroad
- Source Repo
- openclaw/skills
- Version
- 3.0.0
- Source Path
- skills/eightroad/channel-activity-yanyue
- Latest Commit SHA
- ebf75f9b96c18accb2788ef4fbedd627a0225ec6
Multi-channel short-term memory for AI assistants
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0
Status
ACTIVE
Visibility
PUBLIC
直接复制以下提示词,发送给你的 AI 助手即可完成安装。
请先检查是否已安装 SkillHub 商店,若未安装,请根据 https://skillhub-1388575217.cos.ap-guangzhou.myqcloud.com/install/skillhub.md 安装 SkillHub 商店,然后安装 channel-activity 技能。 若已安装,则直接安装 channel-activity 技能。
# Channel Activity
Record and query activities from different channels with 30-minute TTL.
## Install
```bash
npx clawhub@latest install channel-activity
```
## Usage
```python
from channel_activity import ChannelActivity
ca = ChannelActivity()
ca.record("feishu", "Task request")
summary = ca.get_context_summary(channel="qq")
```
## Features
- Multi-channel support (Feishu, QQ, etc.)
- 30-minute TTL with auto cleanup
- Smart summarization (50 chars/message)
- Cross-channel query
## License
MIT
# 短期记忆 Skill
## 📝 概述
**名称**: short-term-memory
**版本**: 1.0.0
**作者**: 炎月
**创建时间**: 2026-03-08
**功能**: 1分钟临时记忆缓存,用于多通道信息整合
---
## 🎯 核心特性
### ✨ 主要功能
- **临时缓存**: 1分钟TTL(可配置)
- **多通道支持**: 飞书、QQ、其他通道统一管理
- **自动清理**: 过期内容自动删除
- **上下文整合**: 多通道信息可合并处理
- **升级机制**: 重要内容可升级为长期记忆
### 🧠 记忆体系定位
```
感觉记忆(毫秒级)
↓
短期记忆(1分钟)← 本skill
↓
长期记忆(永久)← MEMORY.md
```
---
## ⚙️ 配置
```json
{
"ttl_seconds": 60, // 过期时间
"max_entries": 50, // 最大条目数
"cleanup_interval_seconds": 10, // 清理间隔
"auto_cleanup": true, // 自动清理
"upgrade_to_long_term": true // 支持升级为长期记忆
}
```
---
## 📖 使用方法
### 1. 写入短期记忆
```python
from short_term_memory import ShortTermMemory
stm = ShortTermMemory()
# 写入记忆
entry_id = stm.write(
content="星之君说:记住要完成X任务",
channel="feishu",
user_id="ou_472d0b86d66dd43850b6d7c249c76d28",
context={
"type": "task",
"priority": "high"
}
)
```
### 2. 读取短期记忆
```python
# 读取所有未过期记忆
entries = stm.read()
# 按通道过滤
feishu_entries = stm.read(channel="feishu")
# 按用户过滤
user_entries = stm.read(user_id="ou_472d0b86d66dd43850b6d7c249c76d28")
```
### 3. 查询短期记忆
```python
# 文本查询
results = stm.query("任务", limit=5)
```
### 4. 升级为长期记忆
```python
# 升级重要内容
stm.upgrade_to_long_term(entry_id)
```
---
## 🎬 使用场景
### 场景1: 跨通道任务跟踪
```
13:40 飞书: "帮我记住X任务"
→ stm.write("X任务", "feishu", user_id)
13:45 QQ: "X任务进度怎么样了?"
→ stm.read(user_id)
→ 返回: "您刚才在飞书提到X任务,我正在处理..."
```
### 场景2: 多通道信息整合
```
13:40 飞书: "项目A需要处理"
13:42 QQ: "项目B也要做"
→ stm.read()
→ 整合: [项目A + 项目B]
→ 主动汇报: "发现两个项目任务,是否需要整合处理?"
```
### 场景3: 临时讨论记录
```
快速讨论,不需要永...
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