Apache-2.0 multi-agent orchestration plugin for DeepSeek Harness and Codex that splits one goal into isolated, parallel task lanes so a single conversation never has to carry an entire project.
DSH integration
Native runtime
Author-claimed
Safety audit
Unaudited
Last verified
2026-09-01
License
Apache-2.0
01What can it help you accomplish?
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
02How to install into DeepSeek Harness
Not specified by the author
03DSH integration and capability boundaries
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
04Who is it for? When not to use it?
Good for
- 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
Not for
- 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.
05Compatibility, maintenance and safety notes
- 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
06Frequently asked questions
What problem does All in Luna solve?
A single AI conversation that tries to carry an entire project keeps growing in context, lets unrelated work contaminate other work, and can stall the whole flow on one local blocker. All in Luna keeps each task's context separate and runs independent tasks in parallel.
How does it relate to DeepSeek Harness?
It ships as an All in Flash DSH plugin built for DeepSeek Harness (dsh) and Codex, adding a multi-agent orchestration layer above ordinary subagents.
Can each task still use subagents and tools?
Yes. Each task can use its own subagents, tools, Skills, or MCPs — parallel across tasks, recursive inside tasks.
Is it open source?
Yes, the repository is licensed Apache-2.0.
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08Data and sources
It turns the work into independent top-level tasks
This page is generated from the project’s public documentation, repository metadata and a structured parse of DSH Plugins; last verified on 2026-09-01. Found an error? Submit a correction.
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