Search axes let you filter queries according to specific case fields, compared to full-text search which finds terms you enter in any part of the case. Along with the search guide, which documents the available axes, search axis auto-complete exists to make using axes as fast and easy as possible. It is available to all FogBugz On Demand customers using FogBugz Ocelot. Auto-complete will suggest axes and queries as you type, saving keystrokes and preventing misspellings that may hide results. To accept a suggestion, select it and hit tab. Auto-complete does the rest, saving valuable seconds. That doesn’t sound like much, but adding up every search over an entire day ends up being a lot of time to steer towards more productive uses. Perhaps you can make that extra pot of coffee to achieve some kind of caffeine-powered hyper awareness.
Here’s an example of a search axis auto-complete in action:
To find all of the cases assigned to “me”, start typing the “assignedTo:” search axis. By the time “assi” rolls around, there are already auto-complete suggestions. Notice that the entire search axis for the highest ranked suggestion shows up in grey in the search bar. Hitting tab auto-completes that search axis. It even helpfully suggests “me” as the query to pass to that search axis. Another tab and the first search query is set.
Of course, you may have a lot of things assigned to you. Add the Last Edited search axis by typing in a few letters and tab to auto-complete “lastEdited:”. The engine suggests all cases that were last edited “today”. It also provides other suggestions in a drop-down box, which can either be selected by the mouse or the up and down arrows and the tab key. In this case, the query is set to look at everything in the last month.
The more text entered in to a box, the better the auto-complete engine can filter down relevant results. Auto-complete will suggest axes, historical searches, and objects such as the names of projects or milestones. It will also suggest special keywords such as “me” or the date-related keywords such as “today” or “last month”.