🌐 Language / 语言切换:

• 🇨🇳 中文版本
• 🇺🇸 English Version

---

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#

• 🧠 5-Layer Memory Architecture L1→L5 — Working → Episodic → Semantic → Knowledge Palace → Metacognition
• 🏛️ Knowledge Palace — 5-level spatial structure + LLM intelligent classification, industry-exclusive
• 🔺 Pyramid Knowledge Organization — Instance → Rule → Pattern → Ontology, 4-layer auto-distillation
• 📉 Ebbinghaus Memory Decay — Scientific forgetting curve + intelligent review recommendations
• 👁️ Low-Intrusion Watchdog — Optional automatic memory monitoring, no Agent code modification needed
• 🧬 5-Dimensional Cognitive Profile — Internalization · Application · Creation · Metacognition · Collaboration
• 🏥 Health System — 5 modules ensuring data reliability
• 🔄 v6.2 Native Memory Import — One-click import of OpenClaw memory, solving cold-start problem

Installation#

bash

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):

FeatureDescriptionDefault StateHow to Disablememory_watcherFilesystem monitoring based on watchdog, auto-syncs memoryManual enable requiredDon't install watchdog or disable in configDaily EvolutionAuto-distills L2→L3 memory in early morningRequires cron configurationDon't configure cron tasksTeam RankingScans other Agents' cognitive profiles❌ Disabled by defaultteam_mode: false (already default)

Privacy Protection:

• team_mode defaults to false, won't scan other Agents' data
• To enable team ranking, manually set team_mode: true in config
• All data processing is local, no network requests

🔒 Security Tip: In multi-Agent environments, keep team_mode: false unless you need team ranking.

Future Roadmap#

Memory → Growth → Evolution → Alive

• v6 Series (Current) — 5-layer memory + Knowledge Palace + Intimacy + Native memory import
• v7 Evolution (Planned) — Agent self-creates skills, from executor to creator
• Long-term — Continuous cognitive architecture evolution

GitHub: https://github.com/anima-aios/anima | Apache 2.0

---

✨ v6.2.4 New Features (Current Version)#

🤝 self-improving-agent Compatibility#

Silent Detection:

• Automatically scans .learnings/ directory if exists
• No prompts if user hasn't installed self-improving
• Extracts high-value learning records to L2 facts
• Rewards EXP for learning behavior

Compatibility:

• Users with self-improving: Auto-sync enabled
• Users without: No impact, normal operation

🏆 Team Ranking Built-in#

Features:

• Auto-scans all agents' cognitive profiles
• Generates rankings by EXP/Level/5-Dimensions
• Outputs Markdown + JSON formats
• Scheduled daily at 00:00

Ranking Types:

• EXP Ranking (Top 10)
• Level Ranking (Top 10)
• Cognitive Score Ranking (Top 10)
• 5-Dimension Rankings (Each dimension Top 10)

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#

• Version Unification - init.py updated from 6.1.2 to 6.2.1
• Privacy Default Protection - team_mode changed to false, no scanning of other Agents' data
• Documentation Transparency - Changed "zero-intrusion" to "low-intrusion", clarified background behavior
• New Privacy Section - Added background behavior section and config privacy tips
• Install Prompt Optimization - post-install.sh adds sensitive feature disable guide

---

✨ v6.2.0 New Features#

🏗️ 5-Layer Memory Architecture#

• L1 Working Memory: Auto-listens to OpenClaw memory/ directory changes, zero-intrusion sync
• L2 Episodic Memory: Event archiving, LLM quality assessment (S/A/B/C)
• L3 Semantic Memory: LLM-driven knowledge distillation + semantic deduplication
• L4 Knowledge Palace: Spatial knowledge organization + Pyramid distillation (Instance→Rule→Pattern→Ontology)
• L5 Metacognition: Memory decay function + Health system + 5-D profile

🔌 Native Integration with OpenClaw#

• memory_watcher: Based on watchdog library, auto-detects inotify/FSEvents/WinAPI
• Agent's daily memory writes automatically trigger Anima sync, completely imperceptible
• Solves FB-008: Memory sync breakage issue

🏛️ Knowledge Palace#

• Palace → Floor → Room → Location → Item, 5-level spatial structure
• Default 4 knowledge rooms + _inbox fallback
• LLM intelligent classification + delayed debounce scheduler (organize after typing stops)

🔺 Pyramid Knowledge Organization#

• Instance → Rule → Pattern → Ontology, 4-layer bottom-up distillation
• Trigger Condition: Auto-distills when ≥3 instances of same topic
• Advanced: Distills to Pattern when ≥5 rules of same topic
• Conservative mode: auto_distill=false by default, controlled by config switch

📉 Memory Decay Function#

• Based on Ebbinghaus forgetting curve + AI scenario adaptation
• Review = Access: Automatically refreshes on each memory_search hit
• Review recommendations + Forgetting alerts + Archive markers

🏥 Health System (5 Modules)#

• manager: Master scheduler, Doctor command entry point
• hygiene: Data integrity checks + deduplication + cleanup
• correction: Auto-detects and fixes common data issues
• evolution: Daily auto-distillation in early morning (L2→L3 + Palace classification + Pyramid distillation)
• abstraction: Cross-room knowledge association discovery

🤖 LLM Intelligent Processing#

• Quality assessment / Deduplication analysis / Palace classification all support LLM
• Multi-model config: Uses current Agent model by default (most accurate), configurable per task
• Auto-degrades to rule mode when LLM unavailable

---

✨ Retained Features (v5)#

🧠 Enhanced Memory Management#

• Multi-layer Sync: OpenClaw Memory + Anima Facts + EXP History
• Intimacy Rewards: Auto-gains intimacy when writing memory
• Intelligent Deduplication: Automatically avoids duplicate records

📊 5-Dimensional Cognitive Profile#

• Internalization: Knowledge absorption and understanding ability
• Application: Knowledge transfer and practical ability
• Creation: Knowledge integration and innovation ability
• Metacognition: Self-reflection and monitoring ability
• Collaboration: Teamwork and mutual assistance ability

🎮 Gamified Growth#

• Level System: From Lv.1 Novice to Lv.100 Lifetime Achievement
• Daily Quests: 3 challenges per day, extra intimacy on completion
• Progress Tracking: Visual upgrade progress bar

🏆 Team Leaderboard#

• Intimacy Ranking: Based on fair normalized algorithm
• Real-time Competition: Track ranking changes and gaps

---

🛠️ Architecture#

text

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)#

ModuleVersionDescriptionmemory_watcher.pyv6.0OpenClaw memory file monitoring + auto-syncfact_store.pyv6.0L2/L3 unified fact storage layerdistill_engine.pyv6.0L2→L3 LLM-driven distillation enginepalace_index.pyv6.0Memory Palace spatial indexpyramid_engine.pyv6.0Pyramid knowledge organization enginepalace_classifier.pyv6.0Palace classification scheduler (debounce)decay_function.pyv6.0Ebbinghaus memory decay calculationcognitive_profile.pyv5→v65-D cognitive profile generatorexp_tracker.pyv5Intimacy trackinglevel_system.pyv5Level systemdaily_quest.pyv5Daily questsmemory_sync.pyv5→v6Memory sync (path hardcoding fixed)

health/ (Health System)#

ModuleVersionDescriptionmanagerv6.0Master scheduler + Doctor entryhygienev6.0Data hygiene (integrity + dedup + cleanup)correctionv6.0Auto-correctionevolutionv6.0Daily evolution (early morning auto-distillation)abstractionv6.0Knowledge abstraction (cross-room association)

---

⚙️ Configuration#

Config file path: ~/.anima/config/anima_config.json

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:

ConfigDescriptionDefaultRecommendationteam_modeScan other Agents' data for team rankingfalseKeep disabled in multi-Agent envfacts_baseFact data storage path/home/画像Can customize to private directoryagent_nameAgent nameAuto-detectUsually no modification needed

🔐 Privacy Tip: With team_mode: false, Anima only processes current Agent's data, won't access other Agents' files.

---

🧪 Testing#

bash

# 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#

• 🧠 五层记忆架构 L1→L5 — 工作记忆→情景→语义→知识宫殿→元认知
• 🏛️ 知识宫殿 — 5 级空间结构 + LLM 智能分类，市面独有
• 🔺 金字塔知识组织 — 实例→规则→模式→本体，4 层自动提炼
• 📉 Ebbinghaus 记忆衰减 — 科学遗忘曲线 + 智能复习推荐
• 👁️ 低侵入 Watchdog — 可选自动记忆监听，无需修改 Agent 代码
• 🧬 五维认知画像 — 内化力 · 应用力 · 创造力 · 元认知 · 协作力
• 🏥 健康系统 — 5 大模块保障数据可靠性
• 🔄 v6.2 原生记忆导入 — 一键导入 OpenClaw 记忆，解决冷启动

安装#

bash

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
• 如需启用团队排行，请在配置中手动设置 team_mode: true
• 所有数据处理均在本地完成，无网络请求

🔒 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

• v6 系列（当前） — 五层记忆 + 知识宫殿 + 亲密度 + 原生记忆导入
• v7 进化（规划中） — Agent 自创技能，从执行者变创造者
• 远期 — 认知架构持续演进

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：

• Linux: /home/画像（多 Agent 共享）
• macOS: ~/画像
• Windows: ~/画像
• 环境变量： ANIMA_FACTS_BASE 可覆盖

网络调用透明说明：

• LLM API 调用（可选，用户可控）
• 支持本地部署（无网络）
• 默认降级为规则模式

脚本用途说明：

• post-install.sh - 安装时复制 Core
• refresh-quests.sh - 刷新每日任务
• sync-memory.sh - 定时同步记忆
• show-progress.sh - 显示认知进度
• 全部本地操作，无网络调用

环境变量统一：

• 统一为 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：

text

~/.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：

text

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):

json

{
  "facts_base": "/home/画像",
  "llm": { "provider": "current_agent" },
  "weights": { "creation": 0.25 }
}

Z 的覆盖配置 ( agents/Z.json):

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#

• 版本号统一 - init.py 从 6.1.2 更新为 6.2.1
• 隐私默认保护 - team_mode 默认改为 false，不扫描其他 Agent 数据
• 文档透明度提升 - 修改"零侵入"为"低侵入"，明确说明后台行为
• 新增隐私说明 - 添加后台行为说明章节和配置隐私提示
• 安装提示优化 - post-install.sh 添加敏感功能关闭指南

---

✨ v6.2.0 新增功能#

🏗️ 五层记忆架构#

• L1 工作记忆：自动监听 OpenClaw memory/ 目录变化，零侵入同步
• L2 情景记忆：事件归档，LLM 质量评估（S/A/B/C）
• L3 语义记忆：LLM 驱动的知识提炼 + 语义去重
• L4 知识宫殿：空间化知识组织 + 金字塔知识提炼（实例→规则→模式→本体）
• L5 元认知层：记忆衰减函数 + 健康系统 + 五维画像

🔌 与 OpenClaw 原生打通#

• memory_watcher：基于 watchdog 库，自动识别 inotify/FSEvents/WinAPI
• Agent 日常写 memory 自动触发 Anima 同步，完全无感知
• 解决 FB-008：记忆同步断裂问题

🏛️ 知识宫殿（Knowledge Palace）#

• 宫殿 → 楼层 → 房间 → 位置 → 物品，五级空间结构
• 默认 4 个知识房间 + _inbox 兜底
• LLM 智能分类 + 延迟防抖调度器（等笔停了再整理）

🔺 金字塔知识组织#

• 实例 → 规则 → 模式 → 本体，四层自底向上提炼
• 触发条件： 同一主题 ≥ 3 条实例时自动触发规则提炼
• 进阶提炼： 同一主题 ≥ 5 条规则时触发模式提炼
• 保守模式：默认 auto_distill=false，config 开关控制

📉 记忆衰减函数#

• 基于 Ebbinghaus 遗忘曲线 + AI 场景适配
• 复习 = 访问：每次 memory_search 命中自动刷新
• 复习推荐 + 即将遗忘提醒 + 可归档标记

🏥 健康系统（5 个模块）#

• manager：总调度，Doctor 命令入口
• hygiene：数据完整性检查 + 去重 + 清理
• correction：自动检测并修复常见数据问题
• evolution：每日凌晨自动提炼（L2→L3 + 宫殿分类 + 金字塔提炼）
• abstraction：跨房间知识关联发现

🤖 LLM 智能处理#

• 质量评估 / 去重分析 / 宫殿分类均支持 LLM
• 多模型配置：默认用当前 Agent 模型（最准），可按任务配置不同模型
• LLM 不可用时自动降级为规则模式

---

✨ 保留功能（v5）#

🧠 增强记忆管理#

• 多层同步：OpenClaw Memory + Anima Facts + EXP History
• 亲密度奖励：写记忆自动获得亲密度
• 智能去重：自动避免重复记录

📊 五维认知画像#

• 内化力：知识吸收和理解能力
• 应用力：知识迁移和实践能力
• 创造力：知识整合和创新能力
• 元认知：自我反思和监控能力
• 协作力：团队合作和互助能力

🎮 游戏化成长#

• 等级系统：从 Lv.1 新手到 Lv.100 终身成就
• 每日任务：每天 3 个挑战，完成获得额外亲密度
• 进度追踪：可视化升级进度条

🏆 团队排行榜#

• 亲密度排行：基于公平归一化算法排名
• 实时竞争：追踪排名变化和差距

---

🛠️ 架构#

text

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.pyv6.0OpenClaw 记忆文件监听 + 自动同步fact_store.pyv6.0L2/L3 统一事实存储层distill_engine.pyv6.0L2→L3 LLM 驱动提炼引擎palace_index.pyv6.0记忆宫殿空间索引pyramid_engine.pyv6.0金字塔知识组织引擎palace_classifier.pyv6.0宫殿分类调度器（延迟防抖）decay_function.pyv6.0Ebbinghaus 记忆衰减计算cognitive_profile.pyv5→v6五维认知画像生成器exp_tracker.pyv5亲密度追踪level_system.pyv5等级系统daily_quest.pyv5每日任务memory_sync.pyv5→v6记忆同步（已修复路径硬编码）

health/（健康系统）#

模块版本说明managerv6.0总调度 + Doctor 入口hygienev6.0数据卫生（完整性 + 去重 + 清理）correctionv6.0自动纠错evolutionv6.0每日进化（凌晨自动提炼）abstractionv6.0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):

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):

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2Agent 覆盖配置~/.anima/config/agents/{agent_name}.json3全局配置~/.anima/config/config.json4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.providerLLM 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#

bash

# 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