Worked on enhancing the chalk-ai/docs repository by developing comprehensive documentation for materialized and windowed aggregations. Focused on clarifying the correct usage of these aggregation features, the work included creating a dedicated documentation page with practical examples and detailed guidance on configuration parameters such as materialization settings and bucket_duration. Incorporated instructions for cron-based scheduling and CLI triggers to support reliable data backfills and operational consistency. Improvements also addressed documentation structure, including better headers, internal linking, and cross-references. Leveraged technical writing, data aggregation expertise, and Markdown and Python to deliver clear, maintainable resources that improve onboarding and user understanding.