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dsh-prime-orchestrator

Workflow Updated 2026.09.03

Run the following command in DeepSeek Harness:

dsh plugin install mrme000m/dsh-prime-orchestrator

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

Run dsh plugin install mrme000m/dsh-prime-orchestrator in the DeepSeek Harness terminal to install; the source is available at https://github.com/mrme000m/dsh-prime-orchestrator

About this plugin

Coordinating multiple AI sessions by juggling windows and pasting context is slow and error-prone. dsh-prime-orchestrator turns a dsh agent into a true orchestrator: you describe the goal, and the plugin handles delegation, parallel execution, result collection, and state synchronization so a single dsh session drives many workstreams at once.

The plugin ships a full orchestration layer. On the model side, the prime_agent tool covers delegation, monitoring, steering, coordination, persistent-goal management, session branching, and recursive subagent control. On the Web side, the Prime Fleet panel renders live event streams for every running session, lets you drill into transcripts, send prompts, abort or switch models mid-session, and even attach to the same daemon session in a TUI. A Cloudflare Workers AI integration rounds it out: cf_ai_run and cf_ai_models tools give the model direct access to Workers AI tasks (text generation, embeddings, image, speech, classification, and more), while a host-plane LLM adapter registers under the cf-workers-ai-native provider route, streaming OpenAI-compatible chat completions with incremental reasoning blocks and tool-call deltas for models such as DeepSeek V4, GLM-5, and Kimi K2.

If you are pushing a complex coding project through dsh, need to drive several models in parallel for different subtasks, or want a single Web console to oversee every AI workflow, this plugin is built for you. Install and it is live; uninstall and the stock three-column shell returns on the next page load. Unmodified presets are removed with the package; ones you have edited stay in place.

Use Cases

  • Drive multiple models in parallel for distinct coding subtasks within one dsh session
  • Track and steer every AI workflow in real time from the Web fleet panel
  • Let the dsh model invoke Cloudflare Workers AI for text, image, speech, and classification tasks

Best For

  • Developers shipping complex coding projects with dsh
  • Teams that need to coordinate multiple AI model workflows simultaneously
  • Solo engineers who want a single console to oversee every AI session