Ammonite 1.9

Ammonite is an add-on to DEVONthink Pro. While DEVONthink allows you to tag your data, it's search capabilities are currently very limited when it comes to tags and dates. It does not allow to search for documents which are not tagged with a certain tag. Searches for data tagged with multiple tags are possible, but involve opening the find panel, clicking 'Advanced&' and building the query manually. When doing this, you have to type in the tag names and you are not given any clues about available tags. Also searching for documents created/modified at a certain date/in a certain date range is currently not supported by DEVONthink. This is where Ammonite comes in. Ammonite visualizes the tags used in a database or on your filesystem. Tags applied to many documents will appear larger then tags applied to a few documents. This helps you to easily drill down on the information you are looking for. It visualizes dates and file types in separate clouds as well, providing a unified, intuitive interface for building even the most complex queries. Ammonite is easy to use: Left-click on a tag in the cloud to find documents having this tag applied. Right-click to exclude documents with this tag from the result. Combine as many tags in your search as you need. The result is updated immediately. Whenever the query is modified, the matching documents will be displayed. Details about the selected document will be shown as well. From here you can reveal or open them in DEVONthink, Finder or an external application. Tagging does not stop at DEVONthink. Tags may be applied to any file or directory on your filesystem. Ammonite lets you search both DEVONthink and your filesystem with one application. DEVONthink Pro is not required for OpenMeta-only use.
What's new in this version:
Search across multiple DEVONthink databases Search Filesystem and DEVONthink databases at the same time Show number of matching files in tooltip of tag Added config option to hide tags matching fewer than n records Databases may now be re-indexed while building a query Improved speed when navigating result set