Allinluna

dsh plugin --profile my-profile add @zenx0x/allinflash

The easy path: this bundle is published to npm, so the install pulls a prebuilt artifact — no build step runs on your machine and no build approval is needed.

# 1. add the bundle to a profile — --profile my-profile points at $DSH_HOME/profiles/my-profile
dsh plugin --profile my-profile add @zenx0x/allinflash

# 2. verify: the bundle should show up as a layer in the resolved config
dsh --profile my-profile --dump-config

# 3. boot the profile
dsh --profile my-profile

# 1. add the bundle to a profile — --profile my-profile points at $DSH_HOME/profiles/my-profile
dsh plugin --profile my-profile add github:zenx0x/allinluna#<commit-sha>

# 2. verify: the bundle should show up as a layer in the resolved config
dsh --profile my-profile --dump-config

# 3. boot the profile
dsh --profile my-profile

Prerequisites

API key

Not required.

Network access

Not required at runtime.

Language

Python

Verdict reason

on npm with a valid bundle declaration

package.json read

plugins/deepseek-harness/package.json

Rules applied from

docs/user/develop/basic/publish.md

Checked at

2026-08-15

> **Stop running an entire project inside one AI conversation.** Give All in Luna one big goal. It turns the work into independent top-level tasks: **run what can run in parallel, wait only on real dependencies, keep each task's context separate, and bring the results back together.** Each task can still use its own subagents, tools, Skills, or MCPs. **Parallel across tasks. Recursive inside tasks.** Small AI coding tasks are easy. The hard part looks more like this: > “Refactor authentication end to end, including the backend, frontend, migration, tests, and documentation.” At first, everything is fine. Then the agent reads files, edits code, runs tests, starts subagents, handles failures, reads more files, and keeps pushing more execution detail back into the same conversation. After eno