
Warsong, known as '''' in Japan, is a tactical role-playing game developed by Nippon Computer Systems (NCS). The first in the Langrisser series, it blended tactical warfare with RPG elements, similar to the Fire Emblem series. It was initially released for the Sega Genesis console and later the PC Engine CD (in Super CD-ROM² format), the former version being published by Treco in America. The PC Engine version was released under the title Langrisser: The Descendants of Light. It was re-released alongside Der Langrisser (a remake of Langrisser II) in a compilation for the Sega Saturn and PlaySt
via RAWG
Warsong, known as '''' in Japan, is a tactical role-playing game developed by Nippon Computer Systems (NCS). The first in the Langrisser series, it blended tactical warfare with RPG elements, similar to the Fire Emblem series. It was initially released for the Sega Genesis console and later the PC Engine CD (in Super CD-ROM² format), the former version being published by Treco in America. The PC Engine version was released under the title Langrisser: The Descendants of Light. It was re-released alongside Der Langrisser (a remake of Langrisser II) in a compilation for the Sega Saturn and PlayStation. That compilation was released for the PlayStation Network in 2009. A full remake of Langrisser I & II was also released in 2019 on both Sony PlayStation 4 and Nintendo Switch and on PC in 2020, featuring new graphics and BGM and also new playable characters and multiple paths through the game for Langrisser I''.
== Gameplay == The player controls a group of heroes or commanders to accomplish some goals each phase. They are joined with non-controlled allies to battle with enemy commanders. Before each phase, the player can purchase up to eight army units from a single type for every one of its heroes. The type of the available army depends on the hero class (e.g. Griffons can only be purchased by Dragon Knights) and have different prices. At the end of each phase, any surviving army provides some amount of cash for the player to use next time.
Discovered by embedding cosine similarity (sentence-transformers MiniLM, 384-dim).