Fufang Yinhua Jiedu granules (FYJG) is a Traditional Chinese Medicine (TCM) compound formulae preparation comprising ten herbal drugs, which has been widely used for the treatment of influenza with wind-heat type and upper respiratory tract infections. However, the phytochemical constituents of FYJG have rarely been reported, and its constituent composition still needs to be elucidated. The complexity of the natural ingredients of TCMs and the diversity of preparations are the major obstacles to fully characterizing their constituents. In this study, an innovative and intelligent analysis strategy was built to comprehensively characterize the constituents of FYJG and assign source attribution to all components. Firstly, a simple and highly efficient ultra-highperformance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry (UHPLC-QTOF MSE) method was established to analyze the FYJG and ten single herbs. High-accuracy MS/MS data were acquired under two collision energies using high-definition MSE in the negative and positive modes. Secondly, a multistage intelligent data annotation strategy was developed and used to rapidly screen out and identify the compounds of FYJG, which was integrated with various online software and data processing platforms. The inhouse chemical library of 2949 compounds was created and operated in the UNIFI software to enable automatic peak annotation of the MSE data. Then, the acquired MS data were processed by MS-DIAL, and a feature-based molecular networking (FBMN) was constructed on the Global Natural Product Social Molecular Networking (GNPS) to infer potential compositions of FYJG by rapidly classifying and visualizing. It was simultaneously using the MZmine software to recognize the source attribution of ingredients. On this basis, the unique chemical categories and characteristics of herbaceous plant species are utilized further to verify the accuracy of the source attribution of multi-components. This comprehensive analysis successfully identified or tentatively characterized 279 compounds in FYJG, including flavonoids, phenolic acids, coumarins, saponins, alkaloids, lignans, and phenylethanoids. Notably, twelve indole alkaloids and four organic acids from Isatidis Folium were characterized in this formula for the first time. This study demonstrates a potential superiority to identify compounds in complex TCM formulas using high-definition MSE and computer software-assisted structural analysis tools, which can obtain high-quality MS/MS spectra, effectively distinguish isomers, and improve the coverage of trace components. This study elucidates the various components and sources of FYJG and provides a theoretical basis for its further clinical development and application.