KISS Sorcar: A Stupidly-Simple General-Purpose and Software Engineering AI Assistant

Abstract

Large language models can generate code and call tools fluently, yet deploying them as practical assistants for long-horizon software engineering and AI-discovery tasks still exposes persistent gaps: finite context windows, a single mistake that can derail entire sessions, agents that get stuck in dead ends, AI slop, and generated changes that are difficult to review or revert. We present KISS Sorcar, an open-source general-purpose AI agent for long-horizon tasks and AI discovery that doubles as an integrated development environment (IDE). It is built on top of the KISS Agent Framework, a stupidly-simple AI agent framework of roughly 2,900 lines of code for the core agents. The framework addresses the gaps above through a structured system prompt and a five-layer agent hierarchy in which each layer adds exactly one concern: budget-tracked ReAct execution, automatic continuation across sub-sessions via summarization, coding and browser tools with parallel sub-agents, persistent multi-turn chat with history recall, and git worktree isolation so every task runs on its own branch. Engineering principles are encoded in the agent's system prompt.