Shiyi Proactive Agent

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.

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

bash

# 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 --propose

Components

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:

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: 3

Time 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:

text

1. Run proactive-agent: python skills/proactive-agent/scripts/action_suggester.py --next

With HEARTBEAT.md

Add to heartbeat checks:

text

python skills/proactive-agent/scripts/action_suggester.py --next

Example Output

text

[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

1. Trading Assistant: Monitor market hours, suggest buy/sell decisions
2. Content Creator: Remind to publish at optimal times
3. Task Manager: Proactively propose tasks based on schedule
4. 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