Forget Something

Implement forgetting mechanisms for AI systems to manage memory overload, improve performance, and maintain data privacy. Use when working with long-term AI...

Security Scan

The skill is an instruction-only guide for implementing forgetting mechanisms and its requirements and instructions are consistent with that purpose.

Purpose & Capability

The name and description (forgetting mechanisms for AI agents) match the SKILL.md content. All examples and integration points reference agent memory, scheduler, logger, and configuration, which are appropriate for this purpose. No unrelated credentials, binaries, or install steps are requested.

Instruction Scope

The instructions stay focused on memory deletion strategies and OpenClaw integration. They do mention exposing functionality via API and cross-agent forgetting — these are reasonable extension points but imply additional security controls (authentication, authorization, audit logging) that the SKILL.md does not specify. The example code also contains minor implementation bugs (e.g., using Array.filter without reassigning or persisting deletions) but these are correctness issues rather than malicious scope creep.

Install Mechanism

Instruction-only skill with no install spec and no external downloads. Nothing will be written to disk by an installer as part of the skill itself.

Credentials

The skill requests no environment variables, credentials, or config paths. Its described integration uses the agent's existing memory, scheduler, and config, which is proportionate to the stated functionality.

Persistence & Privilege

The skill does schedule recurring forgetting tasks via the agent scheduler (normal for this function). It is not marked always:true. However, scheduled automatic deletion and any API endpoints/cross-agent forgetting capability increase operational risk if not protected — the SKILL.md does not detail access controls or backup storage specifics.

Assessment

This skill is a coherent, instruction-only guide for implementing forgetting strategies. Before installing or enabling it: (1) confirm where backups are stored and that backups are encrypted and access-controlled, (2) require and verify authentication/authorization for any API endpoints that trigger forgetting, (3) test using dryRun and conservative settings to ensure deletions behave as you expect (the examples may not persist deletions as written), (4) add audit logging and retention to track what was removed, and (5) if you enable cross-agent or scheduled forgetting, restrict who can change the schedule or config. If you need, ask the author for concrete storage/backup and API security details before enabling automatic runs.

Forget Something Skill

遗忘机制技能

This skill enables implementation of forgetting mechanisms for AI systems, particularly for OpenClaw agents, to manage memory overload, improve performance, and maintain data privacy. 该技能为AI系统（特别是OpenClaw智能体）实现遗忘机制，用于管理内存过载、提高性能和维护数据隐私。

Overview

概述

Forgetting mechanisms are essential for AI systems that accumulate large amounts of data over time. They help:

• Prevent memory bloat and performance degradation
• Maintain data privacy by removing outdated or sensitive information
• Focus on relevant information by eliminating noise
• Comply with data retention policies and regulations

遗忘机制对于随时间积累大量数据的AI系统至关重要。它们有助于：

• 防止内存膨胀和性能下降
• 通过移除过时或敏感信息来维护数据隐私
• 通过消除噪音来专注于相关信息
• 遵守数据保留政策和法规

Forgetting Strategies

遗忘策略

1. Time-Based Forgetting

1. 基于时间的遗忘

Remove data after a specified time period. 在指定时间段后移除数据。

// Example: Remove memories older than 30 days
// 示例：删除超过30天的记忆
const forgetOldMemories = (memoryStore, days = 30) => {
  const cutoffTime = Date.now() - (days * 24 * 60 * 60 * 1000);
  memoryStore.filter(memory => memory.timestamp > cutoffTime);
};

2. Relevance-Based Forgetting

2. 基于相关性的遗忘

Remove data based on relevance score. 基于相关性分数移除数据。

// Example: Remove memories with relevance score below threshold
// 示例：删除相关性分数低于阈值的记忆
const forgetIrrelevantMemories = (memoryStore, threshold = 0.3) => {
  memoryStore.filter(memory => memory.relevance >= threshold);
};

3. Frequency-Based Forgetting

3. 基于访问频率的遗忘

Remove data based on access frequency. 基于访问频率移除数据。

// Example: Remove memories accessed less than N times
// 示例：删除访问次数少于N次的记忆
const forgetInfrequentMemories = (memoryStore, minAccessCount = 2) => {
  memoryStore.filter(memory => memory.accessCount >= minAccessCount);
};

4. Explicit Forgetting

4. 显式遗忘

Remove specific data based on user requests. 根据用户请求移除特定数据。

// Example: Remove specific memory by ID
// 示例：通过ID删除特定记忆
const forgetSpecificMemory = (memoryStore, memoryId) => {
  memoryStore.filter(memory => memory.id !== memoryId);
};

5. Context-Based Forgetting

5. 基于上下文的遗忘

Remove data based on current context relevance. 基于当前上下文相关性移除数据。

// Example: Remove memories unrelated to current task
// 示例：删除与当前任务无关的记忆
const forgetContextIrrelevant = (memoryStore, currentContext) => {
  memoryStore.filter(memory => {
    return memory.topics.some(topic => currentContext.topics.includes(topic));
  });
};

Implementation for OpenClaw

OpenClaw实现

Memory Store Structure

记忆存储结构

// Example memory structure
// 示例记忆结构
const memory = {
  id: "unique-id-123",
  content: "This is a memory content",
  timestamp: Date.now(),
  relevance: 0.8,
  accessCount: 5,
  topics: ["project", "meeting", "action-item"],
  source: "user-input",
  sensitivity: "low" // low, medium, high
  // 敏感度：低、中、高
};

Forgetting Configuration

遗忘配置

// OpenClaw forgetting configuration
// OpenClaw遗忘配置
const forgettingConfig = {
  strategies: [
    {
      type: "time-based",
      days: 30,
      enabled: true
    },
    {
      type: "relevance-based",
      threshold: 0.3,
      enabled: true
    },
    {
      type: "frequency-based",
      minAccessCount: 2,
      enabled: true
    }
  ],
  runInterval: "daily", // daily, weekly, monthly
  // 运行间隔：每日、每周、每月
  dryRun: false, // preview what would be deleted
  // 模拟运行：预览将要删除的内容
  backupBeforeForgetting: true
  // 遗忘前备份：是
};

Integration with OpenClaw

与OpenClaw集成

// Example integration with OpenClaw agent
// 与OpenClaw智能体集成示例
const OpenClawForgettingMechanism = {
  init(agent) {
    this.agent = agent;
    this.memoryStore = agent.memory;
    this.config = agent.config.forgettingMechanism || {};
    this.setupScheduler();
  },
  
  setupScheduler() {
    const interval = this.config.runInterval || "daily";
    const cronExpression = this.getCronExpression(interval);
    
    // Schedule forgetting based on configuration
    // 根据配置安排遗忘任务
    this.agent.scheduler.addJob({
      name: "forgetting-mechanism",
      cron: cronExpression,
      task: () => this.runForgetting()
    });
  },
  
  getCronExpression(interval) {
    const expressions = {
      daily: "0 0 * * *",
      weekly: "0 0 * * 0",
      monthly: "0 0 1 * *"
    };
    return expressions[interval] || "0 0 * * *";
  },
  
  async runForgetting() {
    this.agent.logger.info("Running forgetting mechanism...");
    
    const originalCount = this.memoryStore.size;
    
    // Apply all enabled strategies
    // 应用所有启用的策略
    this.config.strategies?.forEach(strategy => {
      if (strategy.enabled) {
        this.applyStrategy(strategy);
      }
    });
    
    const finalCount = this.memoryStore.size;
    const removedCount = originalCount - finalCount;
    
    this.agent.logger.info(`Forgetting mechanism completed: Removed ${removedCount} memories`);
    
    return {
      originalCount,
      finalCount,
      removedCount
    };
  },
  
  applyStrategy(strategy) {
    switch (strategy.type) {
      case "time-based":
        this.forgetTimeBased(strategy.days);
        break;
      case "relevance-based":
        this.forgetRelevanceBased(strategy.threshold);
        break;
      case "frequency-based":
        this.forgetFrequencyBased(strategy.minAccessCount);
        break;
      case "context-based":
        this.forgetContextBased(strategy.context);
        break;
      default:
        this.agent.logger.warn(`Unknown forgetting strategy: ${strategy.type}`);
    }
  },
  
  forgetTimeBased(days = 30) {
    const cutoffTime = Date.now() - (days * 24 * 60 * 60 * 1000);
    this.memoryStore.filter(memory => memory.timestamp > cutoffTime);
  },
  
  forgetRelevanceBased(threshold = 0.3) {
    this.memoryStore.filter(memory => memory.relevance >= threshold);
  },
  
  forgetFrequencyBased(minAccessCount = 2) {
    this.memoryStore.filter(memory => memory.accessCount >= minAccessCount);
  },
  
  forgetContextBased(context) {
    this.memoryStore.filter(memory => {
      return memory.topics.some(topic => context.topics.includes(topic));
    });
  },
  
  // Manual forgetting methods
  // 手动遗忘方法
  forgetSpecificMemory(memoryId) {
    return this.memoryStore.filter(memory => memory.id !== memoryId);
  },
  
  forgetByTopic(topic) {
    return this.memoryStore.filter(memory => !memory.topics.includes(topic));
  },
  
  forgetAll() {
    return this.memoryStore.clear();
  }
};

Usage Examples

使用示例

1. Configure Forgetting Mechanism

1. 配置遗忘机制

// In agent configuration
// 在智能体配置中
const agentConfig = {
  // ... other config
  // ... 其他配置
  forgettingMechanism: {
    strategies: [
      {
        type: "time-based",
        days: 30,
        enabled: true
      },
      {
        type: "relevance-based",
        threshold: 0.4,
        enabled: true
      }
    ],
    runInterval: "daily",
    backupBeforeForgetting: true
  }
};

2. Manual Forgetting

2. 手动遗忘

// In agent code
// 在智能体代码中
await agent.forgettingMechanism.forgetSpecificMemory("memory-id-123");
await agent.forgettingMechanism.forgetByTopic("confidential");

3. Run Forgetting on Demand

3. 按需运行遗忘

// Trigger forgetting manually
// 手动触发遗忘
const result = await agent.forgettingMechanism.runForgetting();
console.log(`Removed ${result.removedCount} memories`);

Best Practices

最佳实践

1. Backup Strategy: Always backup memories before running forgetting operations

2. 备份策略：在运行遗忘操作前始终备份记忆

3. Dry Run First: Use dryRun mode to preview what would be deleted

4. 先模拟运行：使用dryRun模式预览将要删除的内容

5. Gradual Implementation: Start with conservative settings and adjust over time

6. 逐步实施：从保守设置开始，随着时间推移进行调整

7. Monitor Impact: Track performance and user experience after forgetting operations

8. 监控影响：在遗忘操作后跟踪性能和用户体验

9. Combine Strategies: Use multiple strategies for more effective memory management

10. 组合策略：使用多种策略进行更有效的记忆管理

11. Privacy Compliance: Ensure forgetting mechanisms comply with data protection regulations

12. 隐私合规：确保遗忘机制符合数据保护法规

Privacy Considerations

隐私考虑

• Right to be Forgotten: Implement explicit forgetting for user requests

• 被遗忘权：为用户请求实现显式遗忘

• Data Minimization: Only retain data that is necessary for the system's purpose

• 数据最小化：只保留系统目的所需的数据

• Sensitive Data: Apply stricter forgetting rules to sensitive information

• 敏感数据：对敏感信息应用更严格的遗忘规则

• Audit Trail: Maintain logs of forgetting operations for accountability

• 审计跟踪：保留遗忘操作的日志以确保问责制

Performance Benefits

性能优势

• Reduced Memory Footprint: Smaller memory stores use less system resources

• 减少内存占用：更小的记忆存储使用更少的系统资源

• Faster Retrieval: Queries run faster on smaller datasets

• 更快的检索：在较小的数据集上查询运行更快

• Improved Relevance: Focus on more recent and relevant information

• 提高相关性：专注于更新的相关信息

• Lower Storage Costs: Reduce storage requirements for long-term operations

• 降低存储成本：减少长期运营的存储需求

Testing and Validation

测试与验证

// Example test for forgetting mechanism
// 遗忘机制测试示例
const testForgettingMechanism = () => {
  // Create test memories
  // 创建测试记忆
  const testMemories = [
    {
      id: "mem1",
      content: "Old memory",
      timestamp: Date.now() - (40 * 24 * 60 * 60 * 1000), // 40 days old
      // 40天前
      relevance: 0.2,
      accessCount: 1
    },
    {
      id: "mem2",
      content: "Recent relevant memory",
      timestamp: Date.now() - (10 * 24 * 60 * 60 * 1000), // 10 days old
      // 10天前
      relevance: 0.8,
      accessCount: 5
    },
    {
      id: "mem3",
      content: "Recent irrelevant memory",
      timestamp: Date.now() - (5 * 24 * 60 * 60 * 1000), // 5 days old
      // 5天前
      relevance: 0.1,
      accessCount: 1
    }
  ];
  
  // Initialize memory store
  // 初始化记忆存储
  const memoryStore = new MemoryStore(testMemories);
  
  // Create forgetting mechanism
  // 创建遗忘机制
  const forgetting = new OpenClawForgettingMechanism();
  forgetting.memoryStore = memoryStore;
  forgetting.config = {
    strategies: [
      { type: "time-based", days: 30, enabled: true },
      { type: "relevance-based", threshold: 0.3, enabled: true }
    ]
  };
  
  // Run forgetting
  // 运行遗忘
  forgetting.runForgetting();
  
  // Verify results
  // 验证结果
  const remainingMemories = memoryStore.getAll();
  console.log(`Remaining memories: ${remainingMemories.length}`);
  console.log(remainingMemories.map(m => m.content));
  
  // Should only keep mem2
  // 应该只保留mem2
  return remainingMemories.length === 1 && remainingMemories[0].id === "mem2";
};

Integration Points

集成点

• OpenClaw Agents: Integrate with agent memory systems

• OpenClaw智能体：与智能体记忆系统集成

• Schedulers: Run forgetting operations on a schedule

• 调度器：按计划运行遗忘操作

• API Endpoints: Expose forgetting functionality via API

• API端点：通过API公开遗忘功能

• User Interfaces: Allow users to configure and trigger forgetting

• 用户界面：允许用户配置和触发遗忘

Future Enhancements

未来增强

• Machine Learning-Based Forgetting: Use ML to predict which memories to forget

• 基于机器学习的遗忘：使用ML预测哪些记忆需要被遗忘

• Adaptive Strategies: Automatically adjust forgetting parameters based on usage patterns

• 自适应策略：根据使用模式自动调整遗忘参数

• Memory Compression: Compress less important memories instead of deleting them

• 记忆压缩：压缩不太重要的记忆而不是删除它们

• Cross-Agent Forgetting: Coordinate forgetting across multiple connected agents

• 跨智能体遗忘：在多个连接的智能体之间协调遗忘

References

参考资料

• Memory Management in AI Systems

• AI系统中的记忆管理

• Forgetting in Artificial Intelligence

• 人工智能中的遗忘

• Data Privacy Regulations (GDPR, CCPA)

• 数据隐私法规（GDPR, CCPA）