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Code comprehension is an inevitable part of the software development process and a frequent target of empirical research. However, the field lacks a shared definition of the construct. Studies operationalize code comprehension in diverse ways, often without explicitly stating what aspect of understanding they measure. As a result, researchers design study-specific tasks and measures, limiting comparability across studies and hindering cumulative knowledge building. To initiate a coordinated approach to assess code comprehension, we introduce a facet-based perspective that distinguishes between analytical skills, abstraction, and critical evaluation. We demonstrate the benefit of explicitly stating the targeted facet(s) of code comprehension and aligning task design accordingly. Building on this perspective, we propose a method to guide researchers from research goals to concrete tasks and study design, including considerations for question formulation and response formats. Rather than immediately prescribing a single standardized instrument, our approach takes a first step toward this long-term goal by enabling researchers to design adaptable yet conceptually grounded measurements. By making operationalizations explicit and tasks reusable, we initiate a cumulative process through which the community can iteratively converge on standardized instruments and, ultimately, a shared understanding of code comprehension.