This codebook provides a structured framework for analyzing how capacity-building is addressed in the National AI Strategies (NASs) of the six GCC countries. It integrates qualitative coding—to categorize references to training, skill development, and organizational capacity—with a TF–IDF analysis that quantifies the emphasis placed on specific AI capabilities (e.g., “Deep Learning,” “Robotics,” “NLP”). By mapping nine thematic categories (such as Infrastructure & ICT, Data Governance & Privacy, and Organizational Capacity) to corresponding survey items, the codebook ensures that policy-level insights align with empirical measures of AI readiness. In practice, researchers flag passages in each NAS that pertain to capacity building, then apply TF–IDF to highlight capabilities that, although mentioned fewer times overall, receive a disproportionately strong focus. Finally, the codebook outlines usage guidelines (how to scope and code relevant passages) and limitations (zero IDF values for universally mentioned terms, possible translation nuances), aiming to standardize document analysis procedures and support reproducible research across AI policy contexts.