This paper introduces a pipeline for analyzing post-secondary course syllabi, leveraging large language models (LLMs). Our approach simplifies traditional labour-intensive and technically demanding syllabi analysis. The analyzer module of this pipeline provides actionable insights, such as competency gap identification and curriculum recommendations, without requiring advanced technical expertise. Case studies across different domains (e.g., career development, computer science, and biology education) were conducted to demonstrate the tool's ability. The results show that the tool produces analysis results that align with educational objectives and suggests improvements, highlighting its potential to streamline curriculum assessment and promote educational effectiveness. Our future plan includes integrating this tool within Learning Management Systems (LMSs) and exploring cross-disciplinary applications to enhance the tool’s utility.