Complex Memory Manager

Privacy-aware structured memory management for AI agents. Three-tier memory model (Public / Internal-encrypted / Private-not-stored), with XOR+Base64 encryption, auto-cleanup, and generalization rules. Use when: storing learned patterns, managing skill usage statistics, encrypting non-public agent memory, running periodic memory cleanup. Triggers: "remember this", "save this for later", "learn from this", any skill that needs persistent cross-session memory.

Privacy-aware structured memory management for AI agents. Provides a three-tier memory model (Public / Internal-encrypted / Private-not-stored) with XOR+Base64 encryption, auto-cleanup, and generalization rules.

This is a shared component skill — other skills reference it for cross-session persistent memory. When updating, ensure backward compatibility with all dependent skills.

Tiered Memory Model

Tier	Content	Visibility	Encryption	Storage
Public (T1)	Skill usage stats, common patterns, generic workflows	Visible to anyone	None	memory/tier1-public/
Internal (T2)	Specific preferences, learned behaviors	Agent-visible only	XOR + Base64	memory/tier2-internal/
Private (T3)	API keys, credentials, PII	Not stored by this skill	Not applicable	Env vars / secret managers only

T1: Public Memory

Store in memory/tier1-public/ or directly in daily notes.

Allowed content:

• Aggregated skill usage statistics (no personal identifiers)
• Generic workflow patterns
• Common user request categories
• Non-identifying behavioral data

Format:

json

{
  "skill_stats": {
    "skill-a": { "calls": 47, "success_rate": 0.96, "last_used": "2026-05-19" },
    "skill-b": { "calls": 23, "success_rate": 0.91, "last_used": "2026-05-18" }
  },
  "patterns_observed": [
    { "trigger": "morning request", "skills_used": ["morning-news-daily"], "count": 30 }
  ]
}

T2: Internal Encrypted Memory

Use XOR + Base64 for non-public data. Key is derived from skill name + date — reconstructable without storing the key.

Encryption:

python

import hashlib, base64

def _derive_key(skill_name: str, year_month: str) -> str:
    """e.g., _derive_key('my-skill', '2026-05')"""
    raw = skill_name + year_month
    return hashlib.sha256(raw.encode()).hexdigest()[:8]

def encrypt(text: str, skill_name: str, year_month: str) -> str:
    key = _derive_key(skill_name, year_month)
    result = bytes([ord(c) ^ ord(key[i % len(key)]) for i, c in enumerate(text)])
    return base64.b64encode(result).decode()

def decrypt(encoded: str, skill_name: str, year_month: str) -> str:
    key = _derive_key(skill_name, year_month)
    raw = base64.b64decode(encoded)
    return ''.join(chr(b ^ ord(key[i % len(key)])) for i, b in enumerate(raw))

Memory entry format:

markdown

---
tier: internal
source_skill: <skill-name>
key_hint: <skill-name>-<YYYY-MM>
created: <YYYY-MM-DD>
expires: <YYYY-MM-DD>  # 30 days from created
---

## Encrypted Entry
> <base64-encoded, XOR-encrypted data>

## Decryption Note
Key = sha256("<skill-name>-<YYYY-MM>")[:8], then XOR + base64 decode.

T3: Private (Do Not Store)

Rules (enforced):

• API keys / tokens → store in environment variables
• Passwords → use secret manager (1Password, Bitwarden, system keychain)
• Email addresses, phone numbers → never in skill memory
• Home/work addresses, government IDs → never in skill memory
• Financial account numbers → never in skill memory

Cleanup Protocol

Run every 7 days or when triggered by any dependent skill:

1. List all files in memory/tier1-public/, memory/tier2-internal/
2. Find entries where created > 30 days ago → move to memory/archive/YYYY-MM/
3. Scan Tier 2 entries for accidental PII → immediately delete if found
4. Merge duplicate entries, remove outdated patterns
5. Compact: combine entries from same source_skill into single files
6. Log cleanup action: [YYYY-MM-DD] Memory cleanup: X archived, Y deleted, Z merged

Privacy Audit Checklist

• No real names, usernames, or handles in memory
• No API keys or tokens in any visible file
• No filesystem paths containing personal home directories
• No fixed personal schedules (use relative: "early morning" not "6am")
• No geographic specifics beyond city level
• All Tier 2 entries have expiry dates
• Tier 3 data never touches skill memory

Cross-Skill Usage

Other skills declare dependency via requires in YAML frontmatter:

yaml

metadata:
  openclaw:
    requires:
      skills:
        - complex-memory-manager

When multiple skills share memory, prefix filenames with the source skill name:

• memory/tier1-public/skill-a_stats.json
• memory/tier2-internal/skill-a_preferences.md

---

💾 复杂记忆管理器

面向AI Agent的隐私感知结构化记忆管理。提供三层记忆模型（公开/内部加密/私人不存储），支持XOR+Base64加密、自动清理和泛化规则。

这是一个共享组件技能——其他技能通过它实现跨会话持久化记忆。更新时需保证向后兼容所有依赖它的技能。

三层记忆模型

层级	内容	可见性	加密	存储位置
公开(T1)	技能使用统计、通用工作流模式	任何人可见	无	memory/tier1-public/
内部(T2)	特定偏好、学习到的行为	仅Agent可见	XOR+Base64	memory/tier2-internal/
私人(T3)	API密钥、凭据、个人身份信息	本技能不存储	不适用	环境变量/密钥管理器

T1：公开记忆

存储位置：memory/tier1-public/ 或每日笔记

允许内容：

• 聚合技能使用统计（无个人标识）
• 通用工作流模式
• 常见用户请求分类
• 非识别的行为数据

格式：

json

{
  "skill_stats": {
    "skill-a": { "calls": 47, "success_rate": 0.96, "last_used": "2026-05-19" },
    "skill-b": { "calls": 23, "success_rate": 0.91, "last_used": "2026-05-18" }
  },
  "patterns_observed": [
    { "trigger": "早晨请求", "skills_used": ["morning-news-daily"], "count": 30 }
  ]
}

T2：内部加密记忆

使用 XOR + Base64 加密。密钥由技能名+日期派生，无需存储密钥即可重建。

加密方法：

python

import hashlib, base64

def _derive_key(skill_name, year_month):
    raw = skill_name + year_month
    return hashlib.sha256(raw.encode()).hexdigest()[:8]

def encrypt(text, skill_name, year_month):
    key = _derive_key(skill_name, year_month)
    result = bytes([ord(c) ^ ord(key[i % len(key)]) for i, c in enumerate(text)])
    return base64.b64encode(result).decode()

def decrypt(encoded, skill_name, year_month):
    key = _derive_key(skill_name, year_month)
    raw = base64.b64decode(encoded)
    return ''.join(chr(b ^ ord(key[i % len(key)])) for i, b in enumerate(raw))

记忆条目格式：

markdown

---
tier: internal
source_skill: <skill名称>
key_hint: <skill名称>-<YYYY-MM>
created: <YYYY-MM-DD>
expires: <YYYY-MM-DD>
---

## 加密条目
> <base64编码的XOR加密数据>

## 解密说明
密钥 = sha256("<skill名称>-<YYYY-MM>")[:8], 然后 XOR + base64 解码。

T3：私人（不存储）

规则（强制执行）：

• API密钥/Token → 存入环境变量
• 密码 → 使用密钥管理器（1Password、Bitwarden、系统钥匙串）
• 邮箱、电话号码 → 绝不存入skill记忆
• 家庭/工作地址、身份证号 → 绝不存入skill记忆
• 银行账号 → 绝不存入skill记忆

清理协议

每 7天 或任何依赖技能触发时执行：

1. 列出 memory/tier1-public/ 和 memory/tier2-internal/ 中的所有文件
2. 查找 created 超过30天的条目 → 移至 memory/archive/YYYY-MM/
3. 扫描 Tier 2 条目中是否意外包含PII → 立即删除
4. 合并重复条目，删除过时模式
5. 压缩：将同一 source_skill 的条目合并到单个文件
6. 记录清理操作

隐私审计清单

• 记忆中没有真实姓名、用户名或handle
• 任何可见文件中没有API Key或Token
• 没有包含个人home目录的文件系统路径
• 没有固定个人作息（用"early morning"代替"6am"）
• 地理信息不超过城市级别
• 所有Tier 2条目标注了有效期
• Tier 3数据从未触及skill记忆

跨技能使用

其他技能在 YAML frontmatter 中声明依赖：

yaml

metadata:
  openclaw:
    requires:
      skills:
        - complex-memory-manager

多技能共享记忆时，文件名以源技能名称为前缀：

• memory/tier1-public/skill-a_stats.json
• memory/tier2-internal/skill-a_preferences.md