The treatment goal for acromegaly has shifted from just hitting biochemical targets of growth hormone (GH) and insulin-like growth factor-1 (IGF-1) remission to a long-term, comprehensive improvement that also considers hormones, metabolic regulations, tumor, symptoms, comorbidities, and patient experience. The SAGIT? assessment system, as the first multi-dimensional clinician-reported outcome tool, integrates five aspects: signs and symptoms (S), associated comorbidities (A), GH levels (G), IGF-1 levels (I), and tumor profile (T). It enables quantitative scoring and dynamic stratification of disease severity. International prospective validation studies have shown that each SAGIT? dimension has good discriminatory ability for disease control; a 2025 multicenter study indicated that SAGIT? objectively reflects disease activity. This article systematically reviews the limitations of existing assessment tools, explains the design principles and scoring criteria of SAGIT?, and discusses its clinical value in disease staging, treatment decision-making, efficacy prediction, and follow-up management. Furthermore, it explores future directions for improving SAGIT? and other disease rating tools, including artificial intelligence integration, development of dynamic monitoring modules, and validation and application in Chinese patients with acromegaly.