It seems pretty useful as a tool for spotting the kind of linguistic howlers that tumble out on first draft. I can see this sort of thing becoming more valuable

It seems pretty useful as a tool for spotting the kind of linguistic howlers that tumble out on first draft. I can see this sort of thing becoming more valuable when more advanced Natural Language Programming APIs become available. It would be cool to see an attempt to encode Orwell's rules from Politics and the English language: (i) Never use a metaphor, simile, or other figure of speech which you are used to seeing in print. (ii) Never use a long word where a short one will do. (iii) If it is possible to cut a word out, always cut it out. (iv) Never use the passive where you can use the active. (v) Never use a foreign phrase, a scientific word, or a jargon word if you can think of an everyday English equivalent. (vi) Break any of these rules sooner than say anything outright barbarous. (https://www.mtholyoke.edu/acad/intrel/orwell46.htm https://www.mtholyoke.edu/acad/intrel/orwell46.htm) I find it quite surprising that detection of cliches and needless multiple-negatives are not common features of word processing software.