proactive-agent

# Proactive Agent Skill

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

### Proactive Behaviors

#### 1. Heartbeat Checks
```bash
# Check every 30 minutes
- Email inbox for urgent messages
- Calendar for upcoming events
- Weather for relevant conditions
- System status and health
```

#### 2. Autonomous Crons
```bash
# Daily maintenance
- Memory compaction and cleanup
- File organization
- Backup verification

# Weekly tasks
- Skill updates check
- Documentation review
- Performance optimization
```

#### 3....