Methodological quality assessment is a pivotal link between primary studies and reliable evidence-based practice, and an essential pathway for operationalizing the core principles of the Guide on Methodological Standards in Pharmacoepidemiology (2nd edition). A prevalent challenge in practice, however, is the conflation of appraising methodological robustness (risk of bias assessment) with verifying reporting transparency (adherence to reporting guidelines). This paper systematically addresses this fundamental challenge, beginning with a clear distinction between the essence and boundaries of these two concepts. On this basis, the article provides a comprehensive review of mainstream quality assessment tools, covering the methodological features and evolutionary trajectory of numerous instruments for interventional (e.g., RoB 2, ROBINS-I), observational (e.g., NOS, the JBI/SIGN/NIH series), secondary (e.g., AMSTAR 2), and other specific types of studies such as health economic evaluations. Furthermore, a complete case study is used to illustrate the practical application of the ROBINS-I tool. The paper's central thesis advocates for an "appraisal-informed design" philosophy, urging a conceptual shift from the retrospective critique of existing literature to the prospective quality control of new research by internalizing appraisal standards as design principles, while also exploring the emerging paradigm of artificial intelligence in assisting assessment. This paper provides a comprehensive methodological reference for researchers and practitioners to prudently select appropriate assessment tools and to conduct rigorous critical appraisals of pharmacoepidemiological evidence.

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