zenx0x/allinluna

All in Luna

简体中文

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.

Why does this exist?

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 enough turns, familiar problems appear:

• the context keeps growing;
• unrelated work starts contaminating other work;
• earlier constraints become easier to forget;
• one local blocker stalls the whole flow;
• subagent results become harder to manage;
• a new conversation has to reconstruct what really happened;
• the agent says “done,” but the outcome may not actually be complete.

All in Luna starts from one simple idea: one conversation should not have to carry an entire project.

One more layer above subagents

A typical agent workflow looks like this:

You
 │
 ▼
Main Agent
 ├─ subagent
 ├─ subagent
 └─ subagent

All in Luna adds a real Top-level Task layer above local workers:

You
 │
 ▼
All in Luna
 │
 ├─ Top-level Task A
 │    ├─ local work
 │    └─ subagents / tools / Skills
 │
 ├─ Top-level Task B
 │    ├─ local work
 │    └─ subagents / tools / MCPs
 │
 └─ Top-level Task C
      └─ waits only when it actually depends on A