web-research

Automate web research by fetching content from known URLs like official documentation, using headless browser automation as a fallback for dynamic pages. This approach requires at least 3 credible sources and outputs a structured report with source URLs, version numbers, and publication dates.

Use headless browser automation as a fallback to scrape dynamic web content when static fetching fails. This two-tier approach prioritizes rapid web fetching for known URLs first, then triggers the headless browser to handle complex searches and dynamic page elements.

A two-tier web fetching strategy works by first attempting rapid content retrieval from known static URLs like blogs and API references. If the content is dynamic or inaccessible, it falls back to headless browser automation to execute searches and render pages.

Yes, automated web research can include version numbers and publication dates in its output. The task prioritizes official documentation and generates a structured research report containing the topic, recommendations, bulleted key findings, and full source URLs.

No, you do not need to provide specific URLs for headless browser research to work. You can simply provide a topic, and the system will first attempt to fetch known documentation references before using headless browser automation for dynamic searches.

The primary limitation of using headless browser automation for web research is its overhead compared to static fetching. It is used strictly as a fallback for dynamic content, meaning static URLs are prioritized first to ensure rapid retrieval before triggering heavier browser automation.