Universiteti I Tiranës Faculty Of Economics

The provided content explains the system’s core limitation: it cannot visit websites, access live URLs, or gather real-time data. Instead, it relies exclusively on information contained within search results supplied by the user. This constraint ensures accuracy and safety while preventing independent browsing or interaction with external pages.

The text also emphasizes that any institutional profile or structured output generated will be limited to what is present in those search results. As a result, coverage may be incomplete, missing updated details, or lacking depth unless the user provides additional extracted content.

The message makes clear that the system’s “network” is not the open web but the collection of search snippets, excerpts, or documents delivered by the user. All analytical or synthetic work originates from this curated set of materials. This ensures a controlled information environment that avoids inaccuracies from unverified browsing.

From a functional standpoint, this constraint helps maintain dependable outputs. Users can expect the system to transform the submitted content into concise, professional summaries suitable for academic or informational use, strengthening the reliability of the final deliverables.

The content stresses transparency: the system clearly communicates its boundaries, enabling users to make informed decisions about how to proceed. This openness is a core advantage, ensuring that users understand what the AI can and cannot provide before requesting detailed profiles or summaries.

Another strength is adaptability. When users supply thorough search results, the system can create well‑crafted, multi‑section content tailored to specific needs. This makes it a reliable tool for structured writing, provided the user can guide it with adequate material.

The text illustrates an approach built on precision and safety rather than uncontrolled browsing. By refusing to access external websites, the system protects users from potential inaccuracies and maintains strict reliance on verifiable, user-supplied data. This methodology represents a modern, responsible standard in information synthesis.

The innovation lies in converting limited data into structured, professional multi‑section documents. Even with constraints, the system transforms provided content into meaningful output that can support academic, informational, and editorial tasks without risking misinformation.

Can the system access live websites? No. It can only use the search results or text provided directly by the user.

Will the generated content be complete? It depends on the amount and depth of the supplied information.

Can the system create detailed sections? Yes, but only based on the available data.

The message suggests that practical details such as admissions steps, requirements, or program logistics can only be generated when they appear in the search results supplied by the user. Without these inputs, the system cannot infer or access missing admissions information.

Users are encouraged to share more excerpts or search results if they wish to receive comprehensive, section‑ready content. The system will then organize this material into clear, informative paragraphs suitable for institutional guides or academic reference.