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dsh-refine

Client Updated 2026.08.21

Run the following command in DeepSeek Harness:

dsh plugin install dushaobindoudou/dsh-refine

Paste the following prompt into your AI chat to install this plugin:

Install the plugin in DeepSeek Harness by running dsh plugin install dushaobindoudou/dsh-refine; the full source repository is https://github.com/dushaobindoudou/dsh-refine .

About this plugin

Refining prompts, memories, skills, and subagents inside dsh often feels like chasing scattered terminal outputs, with no single place to inspect what changed, why it changed, or how to roll it back. dsh-refine fills that gap by porting the prime-agent /refine concept into the dsh ecosystem and wrapping it in a familiar UX layer: a /refine command for quick, instruction-driven refinements, and a settings panel where entries, a refinement timeline, one-click rollback, and auto-gate audit all live side by side.

The command path is deliberately non-blocking. When you type /refine , the engine and agent are validated synchronously, the acknowledgement returns immediately, and the input box is never frozen for a planner round-trip. Results land later in the panel timeline and /refine history. Rollback, by contrast, is fully synchronous: it applies only the stored inverse edits with no LLM call, so undoing the last refinement is a single click. Most importantly, the dsh-continual-harness engine is optional at runtime; without it, every operation degrades into actionable setup guidance rather than an error, and session logs written by the engine stay loadable through a one-time event-type registration with no data migration.

If you manage multiple entry kinds in dsh and want refinement to become an auditable, reversible workflow rather than a stream of ad-hoc edits, dsh-refine adds that lightweight, complete UX layer on top of the existing harness.

Use Cases

  • Quickly roll back a prompt or skill to a previous version with one click instead of manually restoring old content
  • Audit the full refinement timeline and auto-gate decisions in the panel to trace why each change was made
  • Issue a natural-language refinement instruction that runs in the background without freezing the input box, with results arriving later in history

Best For

  • Daily dsh users who manage multiple entry kinds including prompts, memories, skills, and subagents
  • Teams that want refinement to become an auditable, reversible workflow rather than scattered terminal edits
  • Lightweight users who prefer graceful degradation and actionable guidance when the engine is not mounted