An AI-powered writing assistant that researches and generates viral X content using proven copywriting frameworks and algorithm-first strategies.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install tweet-writer
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install tweet-writer using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
The Tweet Writer is a specialized tool designed to transform raw concepts into high-impact social media content. By leveraging Openclaw Skills, this agent performs deep niche research to identify viral patterns and hooks that are currently resonating on X. It moves beyond generic AI writing by analyzing the engagement hierarchy and technical dwell-time requirements of the 2026 X algorithm, ensuring your content is engineered for maximum reach.
This skill is particularly valuable for developers, founders, and marketers who need to maintain an authoritative presence without spending hours on research. It synthesizes real-time web data with classic persuasion principles to produce content that stops the scroll and drives meaningful interaction, making it a cornerstone for anyone building an audience through Openclaw Skills.
To get started with the Tweet Writer, ensure your environment is configured to support Openclaw Skills for research and content generation.
# Initialize the Openclaw Skills environment
openclaw init
# Install the research dependency
openclaw install web-search
# Add the tweet-writer skill to your agent
openclaw skills add tweet-writer
The skill organizes content into structured components to ensure algorithm compatibility and readability.
| Component | Technical Specification | Purpose |
|---|---|---|
| Hook | < 110 characters | Primary scroll-stopper and curiosity gap |
| Core Value | < 250 characters per tweet | Value delivery and information density |
| Thread Structure | Numbered sequence (1/n) | Increasing dwell time and logical flow |
| Engagement Driver | Question or CTA | Maximizing the reply-to-impression ratio |
| Research Metadata | Pattern analysis strings | Guidance for tone and niche-specific triggers |
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