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在 OpenClaw 中安装
/install caring-memory
功能描述
AI task reminder using priority, Ebbinghaus intervals, gamification, and active time tracking for effective task management.
使用说明 (SKILL.md)
Caring Memory Skill
🧠 AI-powered task reminder system with Ebbinghaus forgetting curve + gamification + active time learning
Overview
A smart task management system that:
- Priority-based reminders: urgent/high/medium/low with auto-upgrade near deadlines
- Ebbinghaus curve: reminds at 1h, 24h, 4d, 7d, 15d intervals
- Gamification: XP, levels, streaks, achievements
- Active time learning: tracks when you're most responsive
Usage
Add a task
python3 caring_memory.py add "Task title" [priority] [deadline]
# priority: urgent/high/medium/low
# deadline: ISO format e.g. "2026-04-10T18:00:00"
Complete a task
python3 caring_memory.py complete \x3Cid>
Cancel a task
python3 caring_memory.py cancel \x3Cid>
List pending tasks
python3 caring_memory.py list
Generate reminder summary (for cron)
python3 caring_memory.py remind
View stats
python3 caring_memory.py stats
Record chat activity
python3 caring_memory.py chat
OpenClaw Integration
Recommended Cron Setup
Morning reminder (08:00):
Task: python3 skills/caring-memory-skill/caring_memory.py remind
Schedule: 0 8 * * *
Midday check (12:00):
Task: python3 skills/caring-memory-skill/caring_memory.py remind
Schedule: 0 12 * * *
Evening review (18:00+21:00):
Task: python3 skills/caring-memory-skill/caring_memory.py remind
Schedule: 0 18,21 * * *
Agent Integration
- Session start: Call
chatto record active time - User mentions tasks: Auto-call
add - User says "done": Call
complete - Heartbeat check: Call
remindfor summary
Priority Auto-Upgrade
| Time to deadline | Upgrade |
|---|---|
| \x3C 24h | high → urgent |
| \x3C 48h | medium → high |
| \x3C 96h | low → medium |
Gamification
| Action | XP |
|---|---|
| Complete task | 10 × priority_multiplier |
| Daily streak | +5 bonus |
| Level up | Every 100 XP |
Trigger Words
- "这很重要" → Add as high priority
- "记住这个" → Add task
- "完成了" / "搞定" → Complete task
- "待办" / "任务" → List tasks
安全使用建议
This skill is internally consistent and implements a local, file-based reminder system. Before installing: 1) Review the full caring_memory.py file (the provided snippet was truncated) to confirm there are no network calls or hidden logging/exfiltration in the remainder of the code. 2) Be aware that task data and activity logs are stored as plain JSON files inside the skill folder (not encrypted); do not store sensitive secrets or personally-identifying data there. 3) If you enable the agent integration (auto-calling add/complete/remind), understand the agent may invoke the skill automatically when the configured trigger words appear. If you want tighter control, run reminders only via cron or require manual invocation. 4) Run the script in a limited environment or sandbox if you want to audit behavior first.
功能分析
Type: OpenClaw Skill
Name: caring-memory
Version: 2.0.0
The skill is a legitimate task management system that implements the Ebbinghaus forgetting curve and gamification. The Python script (caring_memory.py) operates entirely on local JSON files for data persistence and lacks any high-risk behaviors such as network requests, shell execution, or access to sensitive system directories. The instructions in SKILL.md are strictly aligned with the stated purpose of automating task reminders and updates for the user.
能力评估
Purpose & Capability
Name/description (task reminder with spaced repetition, gamification, active-time learning) match the files and code: the Python script implements task CRUD, reminder generation, activity logging, priority upgrades and XP rules. No unrelated credentials, binaries, or external services are requested.
Instruction Scope
SKILL.md instructs the agent and cron to run local commands (python3 caring_memory.py ...). It also suggests agent integration patterns (call chat/add/complete/remind on session start or user mentions) — this is within the skill's purpose but grants the agent discretion to invoke the skill automatically when those triggers occur. The instructions and code operate on files in the skill directory only.
Install Mechanism
No install spec (instruction-only / script-based) and no downloads. The skill runs as a local Python script and ships package.json and config.json; nothing is fetched from external URLs during install.
Credentials
The skill declares no required environment variables, credentials, or system config paths. The code reads/writes local JSON files (tasks.json, activity_log.json, stats.json, config.json) in the skill directory — this is proportional to a local task manager.
Persistence & Privilege
always is false and disable-model-invocation is false (normal). The skill stores state in local JSON files in its directory; it does not request elevated platform privileges or modify other skills' configuration.
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install caring-memory - 安装完成后，直接呼叫该 Skill 的名称或使用
/caring-memory触发 - 根据 Skill 的参数说明提供必要输入，即可获得结构化输出
版本历史
v2.0.0
v2.0: Ebbinghaus curve + gamification + active time learning
元数据
常见问题
Caring Memory 是什么？
AI task reminder using priority, Ebbinghaus intervals, gamification, and active time tracking for effective task management. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 99 次。
如何安装 Caring Memory？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install caring-memory」即可一键安装，无需额外配置。
Caring Memory 是免费的吗？
是的，Caring Memory 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
Caring Memory 支持哪些平台？
Caring Memory 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（cross-platform）。
谁开发了 Caring Memory？
由 wukai8289（@wukai8289）开发并维护，当前版本 v2.0.0。
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