Characteristic analysis of parallel job is the basics of workload analysis research. Job accounting log is an important data source of job characteristic analysis, however, existing tools cannot do statistics analysis with application name, because of application name not recorded in job accounting log. To solve this problem, a novel marking method for job accounting log was proposed, which based on keyword fuzzy matching. Combined with a general job data model and a flexible extensible software architecture, a parallel job feature analysis tool JobCAT was implemented. According to verification test by millions of job accounting log data from a supercomputer system, the log marking rate of JobCAT was greater than 95%. JobCAT supports 7 plugins and 29 statistical reports, and can easily make analysis report classified by application name, which has practical value to workload analysis research.