dsh-prime-agent

dsh-prime-agent tackles the core pain points of fragmented tool calls and cumbersome context management in AI-assisted programming. Under traditional one-shot semantics, models must reinitialize the environment for each execution, making variables and state difficult to persist, which disrupts workflow continuity. This plugin introduces a Prime preset for DeepSeek Harness, delivering an RLM-first control plane that simplifies model interaction into a single persistent TypeScript REPL tool. Within this environment, code units execute consecutively like a notebook, with variables and functions from previous units directly available in subsequent ones, allowing models to focus more on logic construction rather than tool switching.

Its core capability lies in a three-layer state management approach: a live namespace that preserves variables within sessions, a latest-completion slot for quick reference, and durable task files for cross-restart checkpoints. This enables natural orchestration of complex workflows—models can sequentially execute side-effectful operations, read in parallel with Promise.allSettled, or offload time-consuming tasks to background jobs while maintaining clear error handling and progress reporting. The plugin also integrates a continual learning layer for optimizing prompts based on interaction experience, though it remains intentionally restrained to avoid interfering with the core process.

dsh-prime-agent is ideal for developers, researchers, and teams deeply engaged in AI programming paradigms who seek reliable automation of complex workflows. If you frequently handle multi-step coding tasks, exploratory data analysis, or cross-session state maintenance in DeepSeek Harness, it can significantly boost efficiency. For users looking to incorporate REPL-style interactions into agentic workflows, this plugin provides a stable and extensible underlying control plane while fully兼容 the existing DSH ecosystem without modifying daily configurations.