OpenFF Parsley 1.0.0, the first version of our Parsley generation of small molecule force fields, achieved excellent coverage of chemical space with a novel direct chemical perception scheme, and similar accuracy to other small molecule force fields, as measured on protein-ligand binding free energies. In contrast to indirect chemical perception, or atom typing, direct chemical perception involves substructure based parameter assignment that brings together complex chemistries under one physically intuitive chemical grouping. SMIRKS patterns are used to define these groups, and the associated parameters can be applied to any substructure match in any molecule, thus making it more general. Rather than having the chemical environment around a parameter being encoded in the atom types, the chemical environment is used to directly assign the parameters via these SMIRKS patterns. This direct chemical perception scheme greatly reduces the number of empirical force field parameters, facilitating rapid refit of parameters to improve chemical accuracy. As atomic partial charges are due to more global effects of chemical environment than SMIRKS strings can provide, another key ingredient of OpenFF force fields is the use of the AM1-BCC model for partial charge assignment, a fast and very widely-used atomic charge model for organic molecules. Our underlying philosophy throughout the OpenFF effort is to combine modern force field optimization techniques and dataset selection pipelines to rapidly produce and update new small molecule force fields.