Web Browsing Assistant

Problem Addressed

When LLMs answer questions about live web content, they can either hallucinate URLs and page details or dump long snippets without reusable structure. Web Browsing Assistant targets this by turning web lookup into an explicit workflow: classify the request as search, URL access, image lookup, or a combination, then call the matching tool to fetch real page information.

How It Works and Limits

• Search tasks: use web_search with concise queries of 1–6 words, keep the query language aligned with the user's request, add a year for time-sensitive topics, and issue at most two independent queries.
• Access tasks: use web_open_url with complete https:// URLs, then extract key points instead of copying long passages.
• Image tasks: use search_image_by_text or search_image_by_image for text-to-image search or image-to-image search with an image URL/local path; text image search defaults to 10 results and supports a maximum of 10.

The output should be structured: tabular or list summaries for data-like content, with original source URLs preserved. If a page is inaccessible, login-gated, region-limited, or contradictory across sources, it should seek alternative sources or state the limitation clearly rather than fabricating content. It fits fact checking, competitor page review, documentation lookup, and lightweight aggregation; it is not a substitute for legal review, deep reverse engineering, or authenticated private-system work.