Abstract In an XML document a considerable fraction consists of markup, that is, begin and end-element tags describing the document&apos;s tree structure. XML compression tools such as XMill separate the tree structure from the data content and compress each separately. The main focus in these compression tools is how to group similar data content together prior to performing standard data compression such as gzip, bzip2, or ppm. In contrast, the focus of this paper is on compressing the tree structure part of an XML document. We use a known algorithm to derive a grammar representation of the tree structure which factors out the repetition of tree patterns. We then investigate several succinct binary encodings of these grammars. Our experiments show that we can be consistently smaller than the tree structure compression carried out by XMill, using the same backend compressors as XMill on our encodings. However, the most surprising result is that our own Huffman-like encoding of the grammars (without any backend compressor whatsoever) consistently outperforms XMill with gzip backend. This is of particular interest because our Huffmannlike encoding can be queried without prior decompression. To the best of our knowledge this offers the smallest queriable XML tree structure representation currently available.