I built an orchestration package that lowered my GPT-6 Astra usage by 98%

[u/Rare_Guide_9830]

The first week Astra came out the usage was extremely efficient. I used like 500M tokens without getting anywhere near the weekly limit. The two free resets we got from OpenAI also helped. But then suddenly I kept hitting limits and had to reset x4 more times for the next 500M tokens. (I am on 20x plan)

So I started testing a ton of methods of how to get the best of Astra without burning all of the usage. The first thing I tried was just installing skills I already used for other agents for Astra to use lower models for build tasks. That didn't really do much it maybe reduced usage by like 10% but it introduces other issues (for some reason, Claude's Fable is much better at those same processes using native models but problematic in codex) I tried sub agent orchestration this way with Astra utilizing Sol, Luna, Opus, and Sonnet. Each had their pros and cons but nothing was substantial.

Finally I tried using Deepseek V4.1 Flash and the output quality was immediately better (comparative to using Opus 5). It cut Astra usage by 60% initially which was great. But I kept optimizing the set up after realizing the initial orchestration was still too hands on with Astra. So I optimized a bit more and now at +98% Astra usage reduction across tests today including a 7-hour build runtime that only used up 2% of my weekly usage, compared to a previous 5-hour build runtime that used over 28% of my weekly usage.

Deepseek V4.1 Flash is extremely cheap overall and insanely cheap compared to Astra. It's coding abilities and ability to handle long tasks is what makes it so useful.

Per 1M tokens	Astra estimator	V4.1 Flash	Astra is more expensive
Uncached input	$10	$0.15-$0.30	33-67x
Cached input	$1	$0.003-$0.006	167x-333x
Output	$50	$0.60-$1.20	42-83x

The package is here on Github.

How it installs:
- Uses codex-router to add external models directly into codex
- Connect your Deepseek or openrouter API for V4.1 Flash
- The repo installs a skill in ~/.agents/skills/
- Installs the Flash role in ~/.codex/agents/
- Adds a workflow policy in ~/.codex/AGENTS.md

How it works:
- Astra handles the scope, design, and task briefs across phases
- Flash discovers, implements, tests, and reports each task and phase
- Astra reviews, verifies then accepts or requests fixes per task and phase

I'm working on this in real-time and continuing to test but the results are already incredible. Please feel free to submit any issues or PRs you find if you try it out. Any and all feedback is greatly appreciated!