glark offers grep-like searching of text files, with very powerful, complex regular expressions (e.g., "/foo\w+/ and /bar[^\d]*baz$/ within 4 lines of each other"). It also highlights the matches, displays context (preceding and succeeding lines), does case-insensitive matches, and automatic exclusion of non-text files. It supports most options from the GNU version of grep.
acoc is a regular-expression based colour formatter for programs that display output on the command-line. It works as a wrapper around the target program, executing it and capturing the stdout stream. Optionally, stderr can be redirected to stdout, so that it, too, can be manipulated. acoc then applies matching rules to patterns in the output and applies colours to those matches.
deplate converts wiki-like markup to LaTeX (standard classes, koma, dramatist, sweave), HTML/PHP (single page, chunked/website, HTML, or s5-based slideshow), DocBook (article, book, man/ref page), and really plain text. Currently supported input formats are viki and Ruby's rdoc. The viki markup supports footnotes, citations, index, table of contents, embedded LaTeX for mathematics, integration with R for dynamically generated figures and tables, and more. Output can be customized via page templates.
AntFlow builds upon Apache Ant to provide a new approach to simplifying system automation that uses pipelines of hot folders chained together to perform a given task. Using XML, it associates an automated task such as data transfer, encryption, or XML processing with a directory on the local system. Whenever a file is copied or written into the hot folder, the associated task is executed and the file is moved to the next hot folder in the pipeline for further processing.
Mailvisa is a spam filter along the lines of Paul Graham's "A Plan for Spam". It classifies messages by comparing the words in them to known spam words. CPU usage, filtering speed, and filtering accuracy are comparable to other Bayesian filters. Mailvisa was originally intended as a platform for experimentation with different filtering parameters, but it has evolved into a useful spam classifier. In the author's own use, the amount of spam caught has surpassed 95% with no false positives so far.