- name
- proactive-agent
- description
- A proactive agent that anticipates needs and takes initiative. Monitors environment, suggests actions, and proposes tasks based on context. Perfect for agents that need to be proactive rather than reactive.
- version
- 1.0.0
- author
- shiyi
- tags
- metadata
- openclaw
- requires
- bins
- [python3]
Proactive Agent
A proactive agent that anticipates needs and takes initiative. Monitors environment, suggests actions, and proposes tasks based on context.
Features
- Context Analysis: Analyzes current time, market status, content pipeline
- Action Suggestion: Predicts needs and generates actionable suggestions
- Task Initiation: Proactively proposes tasks based on context
- Priority Management: 3-tier priority system (Trading > Content > Learning)
Quick Start
# Get next suggested action
python scripts/action_suggester.py --next
# Analyze current context
python scripts/context_analyzer.py --json
# Propose tasks
python scripts/task_initiator.py --proposeComponents
1. Context Analyzer (scripts/context_analyzer.py)
Analyzes:
- Current time slot (morning_startup, trading_hours, content_window, etc.)
- Market status (open/closed)
- Content pipeline status
- Pending tasks
- Recent interactions
2. Action Suggester (scripts/action_suggester.py)
Generates suggestions based on:
- Time-based rules (trading hours, content window)
- Market conditions
- Content pipeline status
- Pending tasks
- Learning optimization needs
3. Task Initiator (scripts/task_initiator.py)
Proactively proposes tasks with:
- Task ID and timestamp
- Priority level
- Step-by-step instructions
- Auto-save to file
4. Proactive Monitor (scripts/proactive_monitor.py)
Continuous monitoring:
- Daemon mode for background operation
- Configurable check intervals
- Alert cooldown management
Configuration
Edit config/proactive_config.yaml:
proactive_level: 7 # 1-10, higher = more proactive
monitor_interval: 300 # Check interval in seconds
alert_cooldown: 1800 # Alert cooldown in seconds
priority_weights:
trading: 10
content: 8
tasks: 6
learning: 4
routine: 3Time Rules
The agent recognizes these time slots:
| Time Slot | Hours | Typical Actions |
|---|---|---|
| morning_startup | 06:00-09:00 | Check portfolio, review today's plan |
| trading_hours | 09:30-15:00 | Monitor stocks, evaluate opportunities |
| content_window | 15:00-17:00 | Publish content, optimize posts |
| evening_routine | 17:00-22:00 | Log daily summary, update memory |
| night_quiet | 22:00-06:00 | Stay quiet, minimal alerts |
Integration
With AGENTS.md
Add to session startup:
1. Run proactive-agent: python skills/proactive-agent/scripts/action_suggester.py --nextWith HEARTBEAT.md
Add to heartbeat checks:
python skills/proactive-agent/scripts/action_suggester.py --nextExample Output
[HIGH] 盘中交易时段
Suggestion: 观察候选股票，等待买入机会
[HIGH] 下午内容发布窗口
Suggestion: 检查待发布内容，准备发布小红书笔记
[MEDIUM] 晚间例行检查
Suggestion: 检查今日数据，记录交易日志Use Cases
- Trading Assistant: Monitor market hours, suggest buy/sell decisions
- Content Creator: Remind to publish at optimal times
- Task Manager: Proactively propose tasks based on schedule
- Learning Agent: Suggest performance analysis and improvements
Requirements
- Python 3.7+
- Works on Windows/Linux/macOS
Changelog
v1.0.0 (2026-03-25)
- Initial release
- Context analyzer, action suggester, task initiator, proactive monitor
- Configuration system
- Time-based rules