A configurable Codex setup where GPT-6 Astra is the root/orchestrator and reviewer, while GPT-5.6 Luna is the default and pinned model for execution subagents.

The installer asks which Codex plan you are on. Pro uses GPT-6 Astra at medium reasoning to orchestrate and GPT-5.6 Luna at max reasoning for execution subagents. Plus uses GPT-5.6 Luna at max reasoning to orchestrate and medium reasoning for execution subagents. Both plans retain the separate GPT-6 Astra reviewer at low reasoning.

Layout

.
├── profiles/
│   ├── pro/
│   │   ├── codex/           (config.toml and agents/*.toml)
│   │   └── agents/          (skills/astra-orchestrator/SKILL.md)
│   └── plus/
│       ├── codex/           (config.toml and agents/*.toml)
│       └── agents/          (skills/astra-orchestrator/SKILL.md)
├── guides/
│   ├── fast-iteration.md
│   ├── complex-repo-work.md
│   ├── routine-coding.md
│   ├── full-orchestration.md
│   ├── plus-plan.md
│   └── token-usage.md
├── scripts/
│   └── token_usage.py
├── AGENTS.md
├── setup.sh
├── setup.ps1
└── LICENSE

Current Plus and Pro configuration

Role or setting	Plus	Pro
Orchestrator	GPT-5.6 Luna — max	GPT-6 Astra — medium
Explorer, worker, tester, researcher	GPT-5.6 Luna — medium	GPT-5.6 Luna — max
Default subagent	GPT-5.6 Luna — medium	GPT-5.6 Luna — max
Independent reviewer	GPT-6 Astra — low	GPT-6 Astra — low
Concurrent subagent limit	4	4

Pro — profiles/pro/codex/config.toml

model = "gpt-6-astra"
model_reasoning_effort = "medium"

approval_policy = "on-request"
sandbox_mode = "workspace-write"

[agents]
enabled = true
max_concurrent_threads_per_session = 4
default_subagent_model = "gpt-5.6-luna"
default_subagent_reasoning_effort = "max"

Plus — profiles/plus/codex/config.toml

model = "gpt-5.6-luna"
model_reasoning_effort = "max"

approval_policy = "on-request"
sandbox_mode = "workspace-write"

[agents]
enabled = true
max_concurrent_threads_per_session = 4
default_subagent_model = "gpt-5.6-luna"
default_subagent_reasoning_effort = "medium"

The installer copies profiles/<plan>/codex to .codex and profiles/<plan>/agents to .agents in the target repository. Each profile is ready to copy, with no configuration rewriting during setup.

Each role file is explicitly pinned to its intended model: Luna for explorer, worker, tester, and researcher; Astra for reviewer. This means changing only default_subagent_model will affect generic spawned agents, but not the named roles.

The four Luna role files explicitly set model_reasoning_effort = "max" in the Pro profile and "medium" in the Plus profile. The reviewer keeps its explicit low effort in both.

When updating an existing installation, copy the role files along with config.toml from the selected profile. Replace <plan> below with pro or plus.

If you want all named roles, including the reviewer, to follow the [agents] defaults, remove both the model and model_reasoning_effort overrides from their role files.

Project setup

Clone this repository:

git clone https://github.com/donvito/codex-astra-luna-orchestrator.git
cd codex-astra-luna-orchestrator

The target project must already exist and must be different from this setup repository.

macOS and Linux

Run the shell installer:

./setup.sh

Windows

Run the PowerShell installer from Windows PowerShell:

powershell -ExecutionPolicy Bypass -File .\setup.ps1

With PowerShell 7, you can use:

pwsh -File .\setup.ps1

Installer prompts

When asked for the target repository, enter its absolute or relative path. For example:

Target repository path: ../my-project

Next, choose your Codex plan:

Codex plan:
  1) Pro  - GPT-6 Astra orchestrates, GPT-5.6 Luna executes, GPT-6 Astra reviews
  2) Plus - GPT-5.6 Luna (max reasoning) orchestrates, GPT-5.6 Luna executes, GPT-6 Astra reviews
Select plan [1/2] (default 1):

The selected configuration sets both the root and default subagent reasoning. Agent role files are shared between plans: explorer, worker, tester, and researcher use Luna at the plan's default effort; the reviewer uses Astra at low effort on both plans.

The installer then asks whether to install each component:

• profiles/<plan>/codex contains the root configuration and agent role profiles, installed as .codex.
• profiles/<plan>/agents contains the astra-orchestrator skill, installed as .agents.
• AGENTS.md gives Codex the project-level orchestration instructions. If it already exists, setup appends the instructions and preserves its contents. Re-running setup skips the append when the same instructions are already present. Symbolic links and incompatible targets are skipped.

Press Enter or answer y to install a component; answer n to skip it. All three components are selected by default.

If a component already exists, the installer lists the exact paths that would be overwritten and asks again before making changes:

WARNING: the following existing files will be overwritten:
  - .codex/config.toml
Update .codex? New files will be added; only paths listed above will be replaced. [y/N]

Existing-file updates default to n. If approved, missing files are added and only the listed paths are replaced. Other files already present in the target component remain untouched.

After setup, launch Codex from the target repository. Project-scoped .codex configuration is loaded only for trusted projects.

See guides/ for copy-paste model presets and the Astra + Luna topology. The guides are intentionally separate from the installers so you can review and adapt settings for your Codex version without changing a global config automatically.

Personal/global setup

For agents, copy the TOML files from profiles/<plan>/codex/agents/ to:

~/.codex/agents/

For the skill, copy profiles/<plan>/agents/skills/astra-orchestrator/ to:

~/.agents/skills/astra-orchestrator/

Merge the settings from profiles/pro/codex/config.toml (Pro) or profiles/plus/codex/config.toml (Plus) into your existing:

~/.codex/config.toml

Do not blindly overwrite your existing global config if you already have MCP servers, providers, permissions, or other settings.

Using the skill

Codex may select the skill automatically when the task matches its description.

You can also invoke it explicitly from Codex CLI or the IDE extension with:

$astra-orchestrator

Example prompt:

$astra-orchestrator

Implement the new invoice export endpoint.
Have explorer map the existing invoice/export path first.
Use workers for bounded implementation, tester for verification,
and reviewer for an independent final review.

Suggested topology

                 GPT-6 Astra
             root / orchestrator
                      |
      +---------------+---------------+
      |               |               |
   explorer          worker         researcher
     Luna             Luna             Luna
      |               |
      +-------+-------+
              |
           tester
            Luna
              |
          reviewer
           Astra
              |
              v
         GPT-6 Astra
      integrate + verify

Tuning

For cheaper/faster runs:

• lower Pro's Astra reasoning from medium to low
• set Luna reasoning to low or medium
• use 3-4 concurrent threads

For larger codebases:

• consider raising Pro's Astra reasoning to high
• start with your plan's Luna default and adjust based on results
• use 6-8 concurrent threads, only when tasks are actually independent

For strict parent/child separation:

• keep explorer/reviewer/researcher read-only
• keep worker/tester workspace-write
• leave the root in workspace-write so it can integrate changes

Token usage

Orchestration is not free: the root stays in the loop for the whole task and every subagent carries its own context. Usage depends on repository size and task shape, so there is no single number. scripts/token_usage.py reads the rollout logs Codex already writes under ~/.codex/sessions and reports usage per thread, role, and model, plus the change in your 5-hour and 7-day rate limit windows:

scripts/token_usage.py --list --date 2026-09-07
scripts/token_usage.py --latest --date 2026-09-07

See guides/token-usage.md for a measurement protocol, one sample run with real numbers, and tips for reducing usage.

Plus users: the root thread is the largest line item, so running it on Luna saves the most. Selecting Plus in the installer does this for you; for a manual or global setup see guides/plus-plan.md:

# Root
model = "gpt-5.6-luna"
model_reasoning_effort = "max"

Important behavior

Explicit model choices during a spawn override [agents] defaults. Custom agent files that specify model or model_reasoning_effort also take precedence over inherited defaults.

The execution role files are pinned to Luna intentionally, while the reviewer is pinned to Astra for independent final review. Astra remains the orchestrator unless you deliberately change the role configuration.

License

Licensed under the Apache License 2.0.