x-engagement

What This Skill Does

The x-engagement skill is an advanced automation framework designed to handle X (formerly Twitter) operations with human-like precision. Unlike basic bots, this skill implements a comprehensive lifecycle management system that includes initial onboarding, persona training, behavioral simulation, a multi-layered memory system, and automated scheduling. It leverages the Chirp engine for stable browser operations, ensuring that all interactions—including scrolling, liking, following, and commenting—mimic natural human patterns to minimize the risk of platform flags. The memory system tracks past interactions and daily logs, allowing the agent to maintain consistent engagement without repeating content or violating persona constraints.

Installation

To install this skill, use the ClawHub CLI in your terminal: clawhub install openclaw/skills/skills/jasoncodespace/x-engagement Once installed, verify the configuration by running ./scripts/check-onboarding.sh. The first time you initiate the skill, it will guide you through a 5-stage setup process, including browser authorization and persona ingestion.

Use Cases

1. Personal Brand Building: Use it to automatically maintain an active presence on X by engaging with followers on the 'Recent' feed according to your pre-defined persona style.
2. Community Management: Automate the daily task of scanning your Following list and providing thoughtful, context-aware comments on relevant industry topics.
3. Trend Monitoring: Utilize the built-in cron job system to aggregate daily hot topics and receive executive summaries, helping you stay ahead of conversations in your niche.

Example Prompts

• "刷推，根据我下午的日程表安排三次互动。"
• "运营推特，重点关注科技领域的新趋势并在以下账号留言：@OpenAI, @AnthropicAI。"
• "去X上互动，帮我检查最新的Feed并挑选5条推文进行回复，记得保持我的一贯幽默风格。"

Tips & Limitations

• Safety First: Always use the docs/comment-rules.md to configure your agent. Avoid aggressive posting frequencies to stay within X's rate limits.
• Persona Training: The accuracy of your agent's interactions depends heavily on the initial 100-tweet learning sample. Choose a representative source for best results.
• Independence: The browser operation is performed via profile=openclaw. Ensure you do not manually manipulate this specific browser profile while the agent is running to prevent session conflicts.
• Monitoring: Regularly check the data/engagement/ folder to review what the agent has posted on your behalf.