MHQL (Minimal Holonomic Quantum Language) provides the semantic foundation for holonomy-first, invariant-only workflows such as the Geometric Quantum Framework (GQF). DOI: 10.5281/ZENODO.18303288 Where GQF introduces an operational methodology for discovering, diagnosing, and promoting native holonomic operations from closed-loop executions, MHQL addresses a logically prior question: What does a loop-based operation mean when only conjugacy-invariant data are accessible, and when is a given semantic tier complete? MHQL formalizes a minimal language of holonomy words, built from calibrated loop primitives and composed using products, inverses, and commutators. The semantics of this language are defined entirely at the level of conjugacy classes, represented operationally by invariant fingerprints (trace moments, overlap-type scalars), without gauge fixing, basis choices, or full operator reconstruction. The contribution of MHQL is not a new geometric phase, a new holonomic gate, or a new control model. Instead, it provides a semantic framework and obstruction result that clarifies the limits of invariant-only reasoning: It defines a minimal, invariant-only semantic layer for loop-based operations; It formalizes small-loop ordering and invariant consistency checks (echoes, palindromes, commutators); It proves that the default single-system semantic tier is incomplete in the presence of entanglement-sensitive loop effects; It introduces entanglement holonomy as a word-level invariant that is operationally accessible yet invisible to any reconstruction based solely on single-system class functions or mode-preserving data. This semantic no-go result directly complements GQF’s operational stance. In GQF, the effective representation on which holonomies act is intentionally left flexible and is promoted only when invariant closure and scaling tests fail. MHQL explains why such promotion must sometimes occur, while GQF provides the diagnostic and operational machinery for detecting this situation and acting on it. Together, MHQL and GQF form a coherent holonomy-first stack: MHQL defines what is meaningful at the invariant level and establishes the semantic limits of single-system descriptions. GQF shows how to discover, certify, and reuse holonomic operations using exactly those invariant-only tools, and how to lift representations when forced by the data. MHQL is therefore not an alternative to GQF, but its semantic and logical foundation. It clarifies when invariant-first workflows are sufficient, when they are not, and why representation lifting in GQF is a semantic necessity rather than a modeling choice.