Anima Aios
by @liruozhou
An AI Agent cognitive growth system built on the native OpenClaw architecture. It provides agents with persistent memory management, visual intimacy progress...
clawhub install anima-aios📖 About This Skill
name: anima-aios description: "An AI Agent cognitive growth system built on the native OpenClaw architecture. It provides agents with persistent memory management, visual intimacy progression, a 5-dimensional cognitive profile, gamified daily quests, team leaderboards, and a 5-layer memory architecture with Knowledge Palace, Pyramid thinking, and Ebbinghaus decay function. 基于 OpenClaw 原生架构的 AI Agent 认知成长体系，为 Agent 提供五层记忆架构、知识宫殿、金字塔知识组织、记忆衰减函数、LLM 智能处理、永久化记忆管理、可视化亲密度成长、五维认知画像、游戏化每日任务和团队排行榜。"
ClawHub Plugin Page Copy (For Reference)
Title
Anima — Give Your AI Agent a Growing SoulSubtitle
Cognitive Science-Based Agent Growth Engine | 5-Layer Memory Architecture | Low-Intrusion InstallationPinned Welcome Message
🌟 Anima — Give Your AI Agent a Growing SoulOne-click install: clawhub install anima-aios
5-Layer Memory · Knowledge Palace · Low-Intrusion · Fully Automatic
Transform your Agent from "restarting every day" to "growing every day"
⭐️ GitHub | Apache 2.0
🌐 Language / 语言切换:
Anima-AIOS v6.0 (English Version)
> Making Growth Visible, Making Cognition Measurable | 让成长可见，让认知可量
Add a 5-layer memory architecture, knowledge palace, cognitive growth, and auto-evolution capabilities to your AI Agent.
Description
Your Agent "restarts every day". Anima changes that.
Anima (Latin for "soul") provides a 5-layer memory architecture for OpenClaw Agents, simulating human cognitive development, enabling Agents to remember experiences, accumulate knowledge, form cognition, and grow continuously.
Core Features
Installation
clawhub install anima-aios
pip install watchdog # Optional: enable automatic memory monitoring
Low-intrusion configuration, optional background monitoring, self-check recommended after installation.
> 💡 Tip: LLM mode supported (intelligent classification/deduplication/quality assessment), automatically degrades to rule mode without LLM.
⚠️ Background Behavior & Privacy
Background Features (disabled or optional by default):
| Feature | Description | Default State | How to Disable |
|---------|-------------|---------------|----------------|
| memory_watcher | Filesystem monitoring based on watchdog, auto-syncs memory | Manual enable required | Don't install watchdog or disable in config |
| Daily Evolution | Auto-distills L2→L3 memory in early morning | Requires cron configuration | Don't configure cron tasks |
| Team Ranking | Scans other Agents' cognitive profiles | ❌ Disabled by default | team_mode: false (already default) |
Privacy Protection:
team_mode defaults to false, won't scan other Agents' datateam_mode: true in config> 🔒 Security Tip: In multi-Agent environments, keep team_mode: false unless you need team ranking.
Future Roadmap
Memory → Growth → Evolution → Alive
GitHub: https://github.com/anima-aios/anima | Apache 2.0
✨ v6.2.4 New Features (Current Version)
🤝 self-improving-agent Compatibility
Silent Detection:
.learnings/ directory if existsCompatibility:
🏆 Team Ranking Built-in
Features:
Ranking Types:
Output:
/home/画像/shared/团队排行榜_{date}.md/home/画像/shared/团队排行榜_{date}.json✨ v6.2.3 New Features (Previous Version)
🔒 Security & Privacy Fixes
✨ v6.2.0 New Features
🏗️ 5-Layer Memory Architecture
🔌 Native Integration with OpenClaw
🏛️ Knowledge Palace
🔺 Pyramid Knowledge Organization
📉 Memory Decay Function
🏥 Health System (5 Modules)
🤖 LLM Intelligent Processing
✨ Retained Features (v5)
🧠 Enhanced Memory Management
📊 5-Dimensional Cognitive Profile
🎮 Gamified Growth
🏆 Team Leaderboard
🛠️ Architecture
Agent Daily Work (OpenClaw write/edit/memory_write)
│
▼ watchdog listens, zero-intrusion
L1 Working Memory ── workspace/memory/*.md
│沉淀
▼
L2 Episodic Memory ── facts/episodic/ (LLM quality assessment)
│提炼
▼
L3 Semantic Memory ── facts/semantic/ (LLM dedup + association)
│结构化
▼
L4 Knowledge Palace ── palace/rooms/ (LLM classification + debounce)
Pyramid ── pyramid/ (Instance→Rule→Pattern→Ontology)
│反思
▼
L5 Metacognition ── 5-D Profile + Intimacy + Decay + Health
📁 Module List
core/ (Core Modules)
| Module | Version | Description | |--------|---------|-------------| | memory_watcher.py | v6.0 | OpenClaw memory file monitoring + auto-sync | | fact_store.py | v6.0 | L2/L3 unified fact storage layer | | distill_engine.py | v6.0 | L2→L3 LLM-driven distillation engine | | palace_index.py | v6.0 | Memory Palace spatial index | | pyramid_engine.py | v6.0 | Pyramid knowledge organization engine | | palace_classifier.py | v6.0 | Palace classification scheduler (debounce) | | decay_function.py | v6.0 | Ebbinghaus memory decay calculation | | cognitive_profile.py | v5→v6 | 5-D cognitive profile generator | | exp_tracker.py | v5 | Intimacy tracking | | level_system.py | v5 | Level system | | daily_quest.py | v5 | Daily quests | | memory_sync.py | v5→v6 | Memory sync (path hardcoding fixed) |health/ (Health System)
| Module | Version | Description | |--------|---------|-------------| | manager | v6.0 | Master scheduler + Doctor entry | | hygiene | v6.0 | Data hygiene (integrity + dedup + cleanup) | | correction | v6.0 | Auto-correction | | evolution | v6.0 | Daily evolution (early morning auto-distillation) | | abstraction | v6.0 | Knowledge abstraction (cross-room association) |⚙️ Configuration
Config file path: ~/.anima/config/anima_config.json
{
"facts_base": "/home/画像",
"agent_name": "auto",
"llm": {
"provider": "current_agent",
"models": {
"quality_assess": "current_agent",
"dedup_analyze": "current_agent",
"palace_classify": "current_agent"
}
},
"palace": {
"classify_mode": "deferred",
"poll_interval_minutes": 30,
"quiet_threshold_seconds": 60,
"retry_delay_seconds": 60
},
"pyramid": {
"auto_distill": false,
"distill_threshold": 3
},
"team_mode": false
}
Key Configuration:
| Config | Description | Default | Recommendation |
|--------|-------------|---------|----------------|
| team_mode | Scan other Agents' data for team ranking | false | Keep disabled in multi-Agent env |
| facts_base | Fact data storage path | /home/画像 | Can customize to private directory |
| agent_name | Agent name | Auto-detect | Usually no modification needed |
> 🔐 Privacy Tip: With team_mode: false, Anima only processes current Agent's data, won't access other Agents' files.
🧪 Testing
# Install dependencies (required for memory_watcher)
pip install "watchdog>=3.0.0"Run integration tests (37 checks)
python3 tests/test_integration_v6.py
_The architecture can only evolve, not degenerate. — Liu Wen's Iron Rule_ _First be honest, then iterate. Code must match the hype. — Qing He_
Anima-AIOS v6.0 (中文版)
> 让成长可见，让认知可量 | Making Growth Visible, Making Cognition Measurable
为你的 AI Agent 添加五层记忆架构、知识宫殿、认知成长和自动进化能力。
描述
你的 Agent 每天都在「重新活一次」。Anima 改变这一点。
Anima（拉丁语「灵魂」）为 OpenClaw Agent 提供五层记忆架构，模拟人类认知发展过程，让 Agent 能记住经历、沉淀知识、形成认知、持续成长。
核心能力
安装
clawhub install anima-aios
pip install watchdog # 可选：启用自动记忆监听
低侵入配置，可选后台监听，安装后建议运行自检。
> 💡 提示：支持 LLM 模式（智能分类/去重/质量评估），无 LLM 时自动降级为规则模式。
⚠️ 后台行为与隐私说明
后台功能（默认关闭或可选）：
| 功能 | 说明 | 默认状态 | 关闭方法 |
|------|------|----------|----------|
| memory_watcher | 基于 watchdog 的文件系统监听，自动同步记忆 | 需手动启用 | 不安装 watchdog 或在配置中禁用 |
| 每日进化 | 凌晨自动提炼 L2→L3 记忆 | 需配置 cron | 不配置 cron 任务 |
| 团队排行 | 扫描其他 Agent 的认知画像 | ❌ 默认关闭 | team_mode: false（默认已关闭） |
隐私保护：
team_mode 默认为 false，不会扫描其他 Agent 数据team_mode: true> 🔒 安全提示：多 Agent 环境下，建议保持 team_mode: false，除非你需要团队排行功能。
未来蓝图
记忆 → 成长 → 进化 → 活着
GitHub: https://github.com/anima-aios/anima | Apache 2.0
✨ v6.2.3 新增功能（当前版本）
🔒 文档透明度提升
多平台路径说明：
/home/画像（多 Agent 共享）~/画像~/画像ANIMA_FACTS_BASE 可覆盖网络调用透明说明：
脚本用途说明：
环境变量统一：
ANIMA_* 前缀OPENCLAW_WORKSPACE 兼容（deprecated 警告）🔧 环境变量统一
变更前：
ANIMA_FACTS_BASE ✅ANIMA_AGENT_NAME ✅OPENCLAW_WORKSPACE ⚠️WORKSPACE ❌变更后：
ANIMA_FACTS_BASE ✅ 主要ANIMA_AGENT_NAME ✅ 主要OPENCLAW_WORKSPACE ⚠️ 兼容（deprecated 警告）✨ v6.2.2 新增功能（上一版本）
🔧 per-Agent 配置覆盖
问题： 多 Agent 场景下，全局配置无法满足个性化需求（如不同的 LLM 配置、五维权重）
解决方案： 支持 per-Agent 配置覆盖
配置结构：
~/.anima/config/
├── config.json # 全局默认配置（所有 Agent 共享）
└── agents/
├── Z.json # Z 的覆盖配置（只写差异）
├── 方秋.json # 方秋的覆盖配置
└── ...
配置合并逻辑：
最终配置 = 代码默认值 + 全局配置 + Agent 覆盖配置
示例：
全局配置 (config.json):
{
"facts_base": "/home/画像",
"llm": { "provider": "current_agent" },
"weights": { "creation": 0.25 }
}
Z 的覆盖配置 (agents/Z.json):
{
"llm": { "provider": "bailian", "models": { "quality_assess": "qwen-max" } },
"weights": { "creation": 0.30 }
}
最终 Z 的配置 = 全局 + Z 覆盖（深度合并）
移除： "agent" 字段（改为运行时自动检测）
优先级： 1. 环境变量（最高） 2. Agent 覆盖配置 3. 全局配置 4. 代码默认值
✨ v6.2.1 新增功能（上一版本）
🔒 安全与隐私修复
✨ v6.2.0 新增功能
🏗️ 五层记忆架构
🔌 与 OpenClaw 原生打通
🏛️ 知识宫殿（Knowledge Palace）
🔺 金字塔知识组织
📉 记忆衰减函数
🏥 健康系统（5 个模块）
🤖 LLM 智能处理
✨ 保留功能（v5）
🧠 增强记忆管理
📊 五维认知画像
🎮 游戏化成长
🏆 团队排行榜
🛠️ 架构
Agent 日常工作（OpenClaw write/edit/memory_write）
│
▼ watchdog 监听，零侵入
L1 工作记忆 ── workspace/memory/*.md
│ 沉淀
▼
L2 情景记忆 ── facts/episodic/（LLM 质量评估）
│ 提炼
▼
L3 语义记忆 ── facts/semantic/（LLM 去重 + 关联）
│ 结构化
▼
L4 知识宫殿 ── palace/rooms/（LLM 分类 + 延迟防抖）
金字塔 ── pyramid/（实例→规则→模式→本体）
│ 反思
▼
L5 元认知层 ── 五维画像 + 亲密度 + 衰减 + 健康
📁 模块清单
core/（核心模块）
| 模块 | 版本 | 说明 | |------|------|------| | memory_watcher.py | v6.0 | OpenClaw 记忆文件监听 + 自动同步 | | fact_store.py | v6.0 | L2/L3 统一事实存储层 | | distill_engine.py | v6.0 | L2→L3 LLM 驱动提炼引擎 | | palace_index.py | v6.0 | 记忆宫殿空间索引 | | pyramid_engine.py | v6.0 | 金字塔知识组织引擎 | | palace_classifier.py | v6.0 | 宫殿分类调度器（延迟防抖） | | decay_function.py | v6.0 | Ebbinghaus 记忆衰减计算 | | cognitive_profile.py | v5→v6 | 五维认知画像生成器 | | exp_tracker.py | v5 | 亲密度追踪 | | level_system.py | v5 | 等级系统 | | daily_quest.py | v5 | 每日任务 | | memory_sync.py | v5→v6 | 记忆同步（已修复路径硬编码） |health/（健康系统）
| 模块 | 版本 | 说明 | |------|------|------| | manager | v6.0 | 总调度 + Doctor 入口 | | hygiene | v6.0 | 数据卫生（完整性 + 去重 + 清理） | | correction | v6.0 | 自动纠错 | | evolution | v6.0 | 每日进化（凌晨自动提炼） | | abstraction | v6.0 | 知识抽象（跨房间关联） |⚙️ 配置 (v6.2.2)
配置结构
全局配置 (~/.anima/config/config.json):
{
"version": "6.2.2",
"facts_base": "/home/画像",
"llm": {
"provider": "current_agent",
"models": {
"quality_assess": "current_agent",
"dedup_analyze": "current_agent",
"palace_classify": "current_agent"
}
},
"palace": {
"classify_mode": "deferred",
"poll_interval_minutes": 30,
"quiet_threshold_seconds": 60,
"retry_delay_seconds": 60
},
"pyramid": {
"auto_distill": false,
"distill_threshold": 3
},
"team_mode": false
}
Agent 覆盖配置 (~/.anima/config/agents/{agent_name}.json):
{
"_comment": "只写与全局配置的差异",
"llm": {
"provider": "bailian",
"models": {
"quality_assess": "qwen-max"
}
},
"weights": {
"creation": 0.30
}
}
配置优先级
| 优先级 | 来源 | 说明 |
|--------|------|------|
| 1 | 环境变量 | ANIMA_FACTS_BASE, ANIMA_TEAM_MODE 等 |
| 2 | Agent 覆盖配置 | ~/.anima/config/agents/{agent_name}.json |
| 3 | 全局配置 | ~/.anima/config/config.json |
| 4 | 代码默认值 | config_loader.py 中的 DEFAULT_CONFIG |
关键配置说明
| 配置项 | 说明 | 默认值 | 建议 |
|--------|------|--------|------|
| team_mode | 是否扫描其他 Agent 数据生成团队排行 | false | 多 Agent 环境保持关闭 |
| facts_base | 事实数据存储路径 | /home/画像 | 可自定义到私有目录 |
| llm.provider | LLM 提供商 | current_agent | 可用 bailian, openai 等 |
| pyramid.auto_distill | 是否启用金字塔自动提炼 | false | 数据量大时可启用 |
> 🔐 隐私提示：team_mode: false 时，Anima 仅处理当前 Agent 的数据，不会访问其他 Agent 文件。
> 💡 提示：Agent 名称自动检测（环境变量 → OpenClaw 上下文 → SOUL.md → 兜底），无需手动配置。
🧪 测试
# 安装依赖（memory_watcher 需要）
pip install "watchdog>=3.0.0"运行集成测试（37 项检查）
python3 tests/test_integration_v6.py
_架构只能演进，不能退化。—— 立文铁律_ _先诚实，再迭代。代码要配得上宣传。—— 清禾_