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Prompts and workflows

GPT-5.6 Luna · workflow

Use Cheap Luna to Orchestrate Threads: Use Threads Rather Than Same-Model Subagents

The author recommends using Luna as a thread orchestrator, letting different threads choose Sol, Terra, or Luna for each task instead of having Sol Ultra automatically generate a batch of equally expensive subagents. The original prompt is very short. Its core。

Source not verifiedGPT-5.6 Luna client or agent harness; confirm the live model entry, tools and version before execution.

Prerequisites and inputs

  • task goal
  • code or product brief
  • runtime constraints
  • acceptance criteria

Task outcome\n\nTurn “Use Cheap Luna to Orchestrate Threads: Use Threads Rather Than Same-Model Subagents” into a checkable starting workflow; do not treat a showcase as general capability.\n\n## Prerequisites\n\n- Prepare the goal, inputs, runtime, and acceptance criteria.\n- Confirm the live GPT-5.6 Luna entry, tool permissions, and version.\n\n## Steps\n\n1. Run a minimal input first and record the model, tools, latency, and failure state.\n2. Check the output against the required format and acceptance criteria, then add missing constraints.\n3. Manually review facts, code, visual artifacts, and external actions.\n\n## Boundary\n\nThis guide is an editorial adaptation of the source observation; it does not claim that Tabbit has verified the source client capabilities.

Read the source research notes

Summary

The author recommends using Luna as a thread orchestrator, letting different threads choose Sol, Terra, or Luna for each task instead of having Sol Ultra automatically generate a batch of equally expensive subagents. The original prompt is very short. Its core idea is use the right model for the task, routing planning, implementation, and documentation research to the appropriate model.

Original prompt

I've been experimenting with using Luna to operate Codex itself. One thread can spawn, steer, and archive other threads… This is a necessary excerpt; read the original source for full context.

Practical constraints

  • Give each thread a clear goal and completion check to prevent the orchestrator from continually creating threads.

  • Record planning, implementation, and research separately so you can verify whether model routing actually occurred.

  • The original post also provides a skill gist: https://gist.github.com/hashimwarren/d2ad4d3a12562dbac8e8f29f0d419999.

  • Comments point out that this may simply add another routing layer and may not be better than native subagents; validate it with task completion time, token usage, and first-pass success rate.

Source and dates

Reddit, r/codex · Source date: Not disclosed · Edited: 2026-09-20

Read the original source
Variable checklist

No required variables

Related prompts

Reddit Codex: Diagnostic and Verification Prompt for Luna Subagent CompatibilityThe Builder's Guide to GPT-5.6: Luna's Model Selection, Agent Orchestration, and CachingReddit Codex: Multi-Model Routing Configuration for Luna Subagents and Sol ReviewX: Create a Custom luna_worker Agent for Codex

Related reviews

Agents on Rails: 8 Models, 21 Atomic TasksThoughts after using GPT-5.6 Luna for 48 hoursGPT-5.6 Luna Is Really Underrated: Codex User Experience5.6 Luna Extra High is the work horse I needed

GPT-5.6 Luna

Use GPT-5.6 Luna in Tabbit

Run this guide in the environment listed above. Downloading does not transfer the template or establish model availability for your account.