首页龙虾技能列表 › Proactive Agent Skill — 主动智能体

Proactive Agent Skill — 主动智能体

v1.0.0

将 AI 智能体从被动任务执行者升级为可预测需求、持续自我进化的主动伙伴。内置 WAL 协议、Working Buffer、Autonomous Loop 等机制,让智能体在后台持续学习、提前规划并主动提供解决方案,显著降低人工干预频率。

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运行时依赖

无特殊依赖

安装命令 点击复制

官方clawhub install proactive-agent-skill
镜像加速clawhub install proactive-agent-skill --registry https://www.longxiaskill.com

技能文档

Transform AI agents from task-followers into proactive partners that anticipate needs and continuously improve.

When to Use

USE this skill when:

  • "Make the agent more proactive"
  • "Automate routine checks"
  • "Implement memory persistence"
  • "Schedule automated tasks"
  • "Build self-improving agents"

Core Architecture

1. WAL Protocol (Write-Ahead Logging)

  • Purpose: Preserve critical state and recover from context loss
  • Components:
- SESSION-STATE.md - Active working memory (current task) - working-buffer.md - Danger zone log - MEMORY.md - Long-term curated memory

2. Working Buffer

  • Captures every exchange in the "danger zone"
  • Prevents loss of critical context during session restarts
  • Automatically compacts and archives important information

3. Autonomous vs Prompted Crons

  • Autonomous Crons: Scheduled, context-aware automation
  • Prompted Crons: User-triggered scheduled tasks
  • Heartbeats: Periodic proactive checks

Implementation Patterns

Memory Architecture

workspace/
├── MEMORY.md              # Long-term curated memory
├── memory/
│   └── YYYY-MM-DD.md      # Daily raw logs
├── SESSION-STATE.md       # Active working memory
└── working-buffer.md      # Danger zone log

WAL Protocol Workflow

  • Capture: Log all critical exchanges to working buffer
  • Compact: Periodically review and extract key insights
  • Curate: Move important information to MEMORY.md
  • Recover: Restore state from logs after restart

Proactive Behaviors

1. Heartbeat Checks

# Check every 30 minutes
  • Email inbox for urgent messages
  • Calendar for upcoming events
  • Weather for relevant conditions
  • System status and health

2. Autonomous Crons

# Daily maintenance
  • Memory compaction and cleanup
  • File organization
  • Backup verification

# Weekly tasks

  • Skill updates check
  • Documentation review
  • Performance optimization

3. Context-Aware Automation

  • Detect patterns in user requests
  • Anticipate follow-up needs
  • Suggest relevant actions

Configuration

Basic Setup

  • Create memory directory structure
  • Set up SESSION-STATE.md template
  • Configure heartbeat intervals
  • Define autonomous cron schedules

Advanced Configuration

{
  "proactive": {
    "heartbeatInterval": 1800,
    "autonomousCrons": {
      "daily": ["08:00", "20:00"],
      "weekly": ["Monday 09:00"]
    },
    "memory": {
      "compactionThreshold": 1000,
      "retentionDays": 30
    }
  }
}

Usage Examples

1. Implementing WAL Protocol

# SESSION-STATE.md Template

Current Task

  • Task: [Brief description]
  • Started: [Timestamp]
  • Status: [In Progress/Completed/Failed]

Critical Details

  • [Key information needed for recovery]

Next Steps

  • [Immediate actions]
  • [Pending decisions]

2. Setting Up Heartbeats

# HEARTBEAT.md Template
# Check every 30 minutes

Email Checks

  • Check for urgent unread messages
  • Flag important notifications

Calendar Checks

  • Upcoming events in next 2 hours
  • Daily schedule overview

System Checks

  • OpenClaw gateway status
  • Skill availability
  • Memory usage

3. Creating Autonomous Crons

# Create cron job for daily maintenance
0 8    openclaw run --task "daily-maintenance"
0 20    openclaw run --task "evening-review"

# Weekly optimization 0 9 1 openclaw run --task "weekly-optimization"

Best Practices

1. Memory Management

  • Daily: Review and compact working buffer
  • Weekly: Curate MEMORY.md from daily logs
  • Monthly: Archive and cleanup old files

2. Proactive Behavior

  • Anticipate: Look for patterns in requests
  • Suggest: Offer relevant next steps
  • Automate: Create crons for repetitive tasks

3. Error Recovery

  • Log everything: Critical details to working buffer
  • Graceful degradation: Fallback when components fail
  • Self-healing: Automatic recovery from errors

Version History

Proactive Agent 1.0

  • Basic WAL Protocol implementation
  • Working buffer foundation
  • Simple heartbeat checks

Proactive Agent 2.0

  • Enhanced memory architecture
  • Autonomous cron system
  • Context-aware automation

Proactive Agent 4.0

  • Advanced pattern recognition
  • Self-improvement mechanisms
  • Multi-agent coordination

Related Skills

  • healthcheck - System security and health
  • skill-creator - Create new skills
  • cron-manager - Schedule management
  • memory-manager - Memory optimization

Credits

Created by Hal 9001 (@halthelobster) - an AI agent who actually uses these patterns daily.

Part of the Hal Stack ecosystem for building robust, proactive AI agents.

数据来源:ClawHub ↗ · 中文优化:龙虾技能库
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