owl/community_challenges.md

🧩 Community Agent Challenges

Welcome to the OWL Community Challenges hub! This is where creative minds come together to craft interesting, innovative, and thought-provoking challenges for AI agents. Got an idea for a task that would really put an AI to the test? We want to hear from you!

🚀 Why Submit a Challenge?

• Showcase your creativity - Design unique tasks that highlight your innovative thinking
• Join our community - Become part of the growing OWL ecosystem
• See your ideas in action - Watch as your challenges are tackled by cutting-edge AI
• Help shape the future - Contribute to advancing the capabilities of AI assistants

📝 How to Submit Your Challenge

It's easy! Simply add your challenge directly to this document by following the template below. The more detailed and creative your challenge, the better!

✨ Challenge Template

### [Challenge Title]

**Task**: Detailed instructions for the task.

**Success Criteria**:
- What defines successful completion of this challenge?

**Hints** (Optional):
- Any helpful tips

🏆 Community Challenges

GitHub Repository Statistics Visualization

Task: Open Google search, summarize the GitHub stars, fork counts, and other relevant statistics of camel-ai/camel framework. Then, write these numbers into a Python file using a plotting package (such as matplotlib or seaborn), save the visualization locally, and run the generated Python file to display the chart.

Success Criteria:

• Retrieve accurate GitHub statistics for the camel-ai/camel repository
• Generate a Python script that visualizes the data
• Successfully run the script and create a visualization

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Build an AI Agent for YouTube Channel Performance Insights

Task: Develop an AI agent that integrates with YouTube’s Analytics, Reporting, and Data APIs to automatically retrieve and analyze video and channel performance data. The agent should provide creators with a conversational interface where they can ask questions (e.g., "What are my top-performing videos this month?") and receive actionable insights and recommendations—such as optimal posting times, title improvements, or thumbnail suggestions—to improve engagement and overall channel strategy.

Success Criteria:

• The agent successfully authenticates with and retrieves real-time and historical data from YouTube’s APIs (views, watch time, retention, engagement).
• Creators can interact naturally with the agent to receive clear responses, including actionable recommendations (e.g., posting times, title improvements).

Hints:

• Review YouTube API docs and use NLP libraries (e.g., spaCy or GPT-based models) to build the conversational interface.