This paper introduces METAGAMER, the first program designed within the paradigm of MetaCame Playing (Metagame) (Pell 1992a). This program plays Metagame in the class of symmetric chess-like games (Pell 1992b), which includes chess, Chinese-chess, checkers, draughts, and Shogi. METAGAMER takes as input the rules of a specific game and analyses those rules to construct for that game an efficient representation and an evaluation function, for use by a generic search engine. The strategic analysis performed by METAGAMER relates a set of general knowledge sources to the details of the particular game. Among other properties, this analysis determines the relative value of the different pieces in a given game. Although METAGAMER does not learn from experience, the values resulting from its analysis are qualitatively similar to values used by experts on known games, and are sufficient to produce competitive performance the first time METAGAMER actually plays each new game. Besides being the first Metagame-playing program, this is the first program to have derived useful piece values directly from analysis of the rules of different games. This paper describes the knowledge implemented in MJSTAGAMER, illustrates the piece values METAGAMER derives for chess and checkers, and discusses experiments with METAGAMJZR on both existing and newly generated games.