A prevailing view of the role motor cortex plays in movement execution is that it’s limited to certain tasks, such as those involving novel muscle activation-patterns. Yet the relevant experimental support remains tenuous and the specific movement features that necessitate motor cortical involvement remain unclear. Classical studies often limited motor cortical function characterition to only a small number of qualitatively-defined movement types. Certain results suggest a broad motor cortical involvement in ensuring the smoothness/agility of many or all movements. Recent studies have raised the possibility that the involvement of motor cortical output may change as movements are repeatedly practiced, calling into question the generalization of findings from well-trained, stereotyped movements. To address this persistent ambiguity regarding motor cortical influence, we combineed a new naturalistic climbing paradigm, rapid optogenetic silencing, forelimb electromyography, large-scale multielectrode array recording, and dimensionality-reduction-based analyses. To overcome the lack of trial structure during self-driven-climbing and achieve statistical power, muscle activity-states were embedded on a low-dimensional map via UMAP (Uniform Manifold Approximation and Projection). Rapid optogenetic silencing of the caudal forelimb area (CFA; forelimb M1) throughout climbing was used to characterize the direct influence of motor cortical output across these maps (‘inactivation mapping’). Visualization of the map-regions showing significant CFA influence on each of four limb-muscles revealed that influence vaired greatly across muscle-states. By aligning CFA neural activity with inactivation maps and developing methodolgy based on singular vector canonical correlation analysis (SVCCA), we found that neural activity within a low-dimensional subspace could almost perfectly predict inactivation effects. It thus appears that activity within this subspace steers climbing in a movement-specific manner. What emerges is a picture in which motor cortical output contributes to particular forms of muscle output that can be deployed throughout naturalistic movement, with influence on each muscle defined by activity variation within a low-dimensional subspace.