採 Apache-2.0 授權、適用於 DeepSeek Harness 與 Codex 的多智慧體編排外掛，把一個目標拆成隔離的平行任務通道，讓一次對話不必承載整個專案。
DSH 整合
原生執行環境
作者聲明
安全稽核
未稽核
最後核實
2026-09-01
授權條款
Apache-2.0
01它能幫你完成什麼？
Orchestrate a large multi-part engineering goal (e.g. refactor authentication end to end) as independent parallel tasks
Independent top-level tasks run in parallel with separate contexts, waiting only on real dependencies, with results merged back together
Developers using DeepSeek Harness (dsh) or Codex who want to split one big goal into isolated, parallel task lanes
Let each task drive its own subagents, tools, Skills, or MCPs while keeping contexts isolated
Each task executes with its own scoped subagents, tools, Skills, and MCPs, recursively, without contaminating other tasks
AI coding agents and developers needing recursive multi-agent workflows without a single growing conversation
02如何將外掛接入 DeepSeek Harness？
作者未說明
03DSH 整合程度與能力邊界
First-class All in Flash DSH plugin: a DeepSeek Harness (dsh) / Codex multi-agent orchestration layer that breaks one goal into independent, parallel task lanes.
Parallel task orchestration
one large goal or prompt→independent top-level tasks executed in parallel with isolated contexts, dependencies respected, results merged
Per-task subagents, tools, Skills, and MCPs
each top-level task→task-scoped subagents, tools, Skills, and MCPs executed recursively
each task maintains its own separate context, isolated from other tasks
04適合誰？何時不該用？
適合
- Developers using DeepSeek Harness (dsh) or Codex who want to split one big goal into isolated, parallel task lanes
- AI coding agents and developers needing recursive multi-agent workflows without a single growing conversation
不適合
- Without task isolation, unrelated work contaminates other work and earlier constraints become easier to forget; All in Luna keeps each task's context separate to avoid this.
05相容性、維護與安全提醒
- Without task isolation, unrelated work contaminates other work and earlier constraints become easier to forget; All in Luna keeps each task's context separate to avoid this.
Apache-2.0 · latest release allinflash-v0.2.0 (2026-08-14), last push 2026-09-01
06常見問題
All in Luna 解決了什麼問題？
把整個專案放在一次 AI 對話裡，會讓上下文不斷增長，無關工作互相污染，也可能因為一個局部阻塞而拖垮整個流程。All in Luna 讓每個任務保持獨立上下文，並平行執行相互獨立的任務。
它與 DeepSeek Harness 的關係是什麼？
它以 All in Flash DSH 外掛形式發布，專為 DeepSeek Harness（dsh）與 Codex 打造，在一般子智慧體之上增加一層多智慧體編排。
每個任務還能使用子智慧體與工具嗎？
可以。每個任務都能使用自己的子智慧體、工具、Skills 或 MCP——任務之間平行，任務內部可遞迴。
它是開源的嗎？
是的，程式庫採用 Apache-2.0 授權。
07相關的 DSH 工作流程
archify
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為編碼智慧體生成美觀可驗證的架構圖、時序圖與資料流圖，輸出自包含 HTML，支援動效與清晰匯出。
openviking
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為 AI 智慧體打造的自進化上下文資料庫，統一智慧體記憶、知識 RAG 與技能。
nocobase
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開源的 AI + 無程式碼應用搭建平臺：AI 在久經生產驗證的底層基礎設施與所見即所得的無程式碼介面之上工作，幫你快速構建 CRM、ERP 等業務系統，兼顧速度與可靠性。
learn-harness-engineering
作者 walkinglabs
Harness 工程新手教程，從 0 到 1 系統學習智慧體工作流框架。
08資料與來源
It turns the work into independent top-level tasks
此頁面根據專案公開文件、儲存庫中繼資料與 DSH Plugins 的結構化解析所產生；最後核實於 2026-09-01。發現錯誤？提交更正。
最佳 DeepSeek Harness 外掛
從全目錄挑出的 12 個值得優先安裝的外掛，涵蓋各個分類。