Personally I think that expecting OpenCV will contain a complete framework for finding textureless objects is rather rediculous. Looking at all the most recent computer vision conferences, still many PhD research goes into solving this exact problem. Basically what you do is implementing the algorithm suggested in a paper, by using openCV as a background.
This means that you will need to spit out every paper you are interested in, look for all subfunctionality and hope that it is implemented in OpenCV. Then use those functionality to combine them smartly into the desired algorithm.
The purpose of OpenCV as I see it is to provide computer vision building blocks, not complete ready served algorithms, because this would limit the options for devellopers. So remarks like, if it is not documented in OpenCV I can't use it, is a rather lame excuse. It just means that you are not prepared to expand existing functionality with new code added.
ADDITION:
Looking for textureless objects can be done by using object categorization techniques, which do not depend on texture, like cascade classifiers, SVM algorithms, random forests, which are all available in OpenCV. They depend on shape features, rather then on texture features.
And to add a last comment, your remark about 'pretty bad documentation' can be countered. OpenCV is a open-source project that relies on the help of its community to devellop everything further. This means that if you have problems with documentation, you file a feature request on the dev forum and if you are really motivated, you add a pull request with the suggested adaptations.