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sharbelxyzAI agent for end-to-end YouTube content strategy and growth
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A YouTube growth agent built with OpenClaw, Nova automates end-to-end content strategy for creators. It addresses the time-consuming tasks of competitor analysis, idea generation, scriptwriting, and performance tracking, aiming to accelerate channel growth and monetization. The agent is designed for YouTube creators of any size, offering significant time savings and data-driven insights to improve video performance.
How It Works
Nova operates as an AI agent within the OpenClaw framework, employing a multi-system approach. It performs competitor scanning to identify high-performing videos, analyzes the user's own channel for patterns, and generates research-backed video ideas through creator interviews. The agent then writes full scripts with SEO packages and logs video performance post-publishing. A key feature is its learning loop, which continuously reads memory files (approved/rejected ideas, performance data) before each session to refine suggestions and prevent repetition of failed angles, ensuring personalized and evolving strategy.
Quick Start & Requirements
https://github.com/sharbelxyz/nova-youtube-agent) to your OpenClaw agent.git clone https://github.com/sharbelxyz/nova-youtube-agent.git ~/clawd/skills/nova-youtube-agent) and then instruct OpenClaw to "Install Nova".https://github.com/sharbelxyz/nova-youtube-agentHighlighted Details
memory/ files for continuous improvement.Maintenance & Community
The project is built by Sharbel, described as a founder, AI builder, and creator. No specific community channels (like Discord or Slack) or formal maintenance structures are detailed in the README.
Licensing & Compatibility
The project is released under the MIT license, which permits free use, modification, and sharing. It is compatible with commercial use and closed-source linking without explicit restrictions.
Limitations & Caveats
Nova requires the OpenClaw framework to function. It does not automate the filming or publishing process; these remain manual tasks for the user. While personal data is kept private on the user's machine via gitignored configuration and memory files, the agent's effectiveness is tied to the quality of the chosen AI model and the user's input during onboarding and interaction.
1 month ago
Inactive
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