Molecular subtype classification of heterogeneous breast cancer is crucial for personalized therapies yet is limited by the low specificity of conventional single-target diagnosis systems. Herein, we developed a compact and versatile catalytic DNA computing (CDC) circuit as a programmable cancer evaluator for efficient dual-microRNA (miRNA) detection, enabling precise breast cancer subtype identification in clinical samples through a sequentially amplified multiplexed molecular imaging technique. Using an innovative and exquisite probe-concatenating and grafting strategy, the compact CDC system was engineered with minimal strand complexity, incorporating only two tandem-caged probes to form two distinct catalytic hairpin assembly (CHA) circuitry modules: pre-CDC and post-CDC modules. These CHA-based modules were sequentially activated by multiple miRNAs, enabling localized cascade signal amplification for the cancer subtype evaluation. Through systematic experimental validation and complementary theoretical simulations, we elucidated the sequential reaction mechanism and discovered the reaction kinetic confinement of the upstream pre-CDC module on the downstream post-CDC module activation. These findings provided valuable insights into the molecular reaction processes and offered critical guidance for designing efficient CDC probes. With its comprehensive multianalyte recognition and synergistic cascade amplification capabilities, the compact CDC circuit enabled the magnified detection of multiple miRNAs within cancer cells. The CDC platform demonstrated exceptional specificity in identifying clinical cancer tissues, making it a robust cancer cell subtype evaluator for breast cancer. Due to its high accuracy and reliability, this molecular evaluator serves as a promising diagnostic tool with potential applications in clinical diagnosis and disease-related molecular mechanism studies.