Industrial robots can perform motion with sub-millimeter repeatability when programmed using the teach-and-playback method. While effective, this method requires significant up-front time, tying up the robot and a person during the teaching phase. Off-line programming can be used to generate robot programs, but the accuracy of this method is poor unless supplemented with good calibration to remove systematic errors, feed-forward models to anticipate robot response to loads, and sensing to compensate for unmodeled errors. These increase the complexity and up-front cost of the system, but the payback in the reduction of recurring teach programming time can be worth the effort. This payback especially benefits small-batch, short-turnaround applications typical of small-to-medium enterprises, who need the agility afforded by off-line application development to be competitive against low-cost manual labor. To fully benefit from this agile application tasking model, a common representation of tasks should be used that is understood by all of the resources required for the job: robots, tooling, sensors, and people. This paper describes an information model, the Canonical Robot Command Language (CRCL), which provides a high-level description of robot tasks and associated control and status information.