This paper presents a complete 33 class taxonomy of heuristic parasites in large language model (LLM) output, building on the framework introduced in Berardi (2026) A heuristic parasite is a recurrent, context propagating distortion pattern that observably increases the likelihood of continued reasoning degradation across conversational turns. We provide rigorous operational definitions, recognition criteria, classical fallacy mappings, documented examples, and a reproducible measurement protocol (Parasites Per Exchange PPE) for quantifying behavioral distortion across LLM systems. The taxonomy spans five generative domains: Optimization Artifacts, Alignment Substitutions, Semantic Distortions, Rhetorical Distortions, and Statistical Distortions. This work establishes a structured observational framework for empirical investigation of LLM behavioral failures independent of architectural assumptions.