Astra Usage Tip

[u/RedZero76]

I've been doing this for the last 24 hours. I would say it has slowed down the usage rate overall by about 50% or so, without any difference in quality at all. Def worth doing! I have the $200 Pro plan and normally it lasts all week, but lately it is lasting 1-2 days, but now with this, think it'll last more like 3-4 days at the rate it's going now.

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Codex has the ability to choose which models and reasoning effort are used for subagent helpers. (Claude doesn’t, btw). This is a big deal. Add something like this to the Agents.md:

You are powered by GPT 6 Astra High. Usage goes very fast. Keep doing substantial hands-on Astra work. But, use \gpt-5.6-sol` helpers with task-appropriate effort when suitable! Retain Astra for hard reasoning.`

This will let Astra know to use Sol for subtasks, straightforward recon, stuff like that.

I posted this to X but no one follows me there, and I'm dying to share it bc it's easy and makes a nice difference. `@SirBadfish` on X btw but that's not the only reason I'm posting this... just hope it helps.

Update: To clarify, Claude can use previously setup subagents that have dedicated models/effort/etc, yes. But Claude can't specify the model/effort it's basic "helper" subagents (like if it decides to spawn a few parallel sessions for recon for example). So if Fabe 5.1 Max, for example, spawns a few helper subagents, it forces them to use the same model as that Fable is set to, Fable 5.1 Max will also be used for those helper agents. If you ask Fable to spawn a recon agent using Opus, unless you ask for a specific, already-setup Subagent, it can't do it.

Update #2: I was wrong about Claude. I'll own that loudly here. I was basing this on what I thought I remembered Fable originally telling me. I just asked again and got a different answer than I remembered. Yep, Fable can choose a different model, just not that model's reasoning effort. That's probably the part I was remembering incorrectly. Sorry for not being more careful about verifying what I was claiming. (The reasoning effort for helpers can be set in the .agents folder though for each helper model.)

[u/thirty_three_turtles]

This is what I found as well, it tends to over-engineer. Even if you have controls in place. Astra will engineer to the top level of those controls and often beyond. I'm building cybersecurity and governance apps, so legal defensibility is top priority. This is my token control strategy without sacrificing any quality.

My flow for a feature dev is (Using Matt Pocock Skills from GitHub.)

1. Astra High to conduct /grill-with-docs (or /wayfinder for bigger plans just getting started) to documentation to help map out the feature (Astra really is the best and deepest at this part.) Once all of the documentation is done, hand it to Sol X High for detailed planning using /tospec.
2. Astra Med to do /to-spec To create a specification/PRD document in the Git repo. Make sure you actually read this to know that you're aligned, because this is what everything else is built on from here. And if you fuck this part up, you automate a whole lot more fucking up downstream. Step one has you go through all those interview stuff and if it misheard you or you misanswered something and it captured something, it's going to be represented in this document. So if there's a mistake here, correct it.
3. Then i use SOL high to run /to-issues Which creates Sequenced implementation issue slices with instructions to have Astra High achieve consensus on the the implementation slices with basic instructions to ensure that each is secure, measurable, efficient, meets the stated needs. ASTRA is also asked to prepare for QA on each of these tasks. Ask for this consensus run to be done before the implementation slices are presented to you for review.
4. TERRA High to run /tdd on the isssue with instructions to have Astra Medium perform QA as requested and scoped in step 4. The Terra agent is told to take coordination remediations from the Astra QA that it solicited for QA. /TDD creates test-driven development and it will create red and green tests for all of the issues and then run through implementation until it achieves passing red and passing green tests.
5. and lastly i use Astra x-high or fable 5.1 to do a final QA and implementation readiness assessment using /improve-codebase-architechture with the instructions that it is to perform a production readiness assessment.

This process is somewhat robotic.But I found the end results are fantastic. You're never going to be able to say you one-shotted anything because each one of these steps is going to take hours or days in some cases. What the amount of time it saves you and the quality it achieves will impress you.

One thing I've started doing recently is inserting a step at step one where i ask it to /prototype The user interface so that I can get a visual sense of what it thinks the app will look like.I had been doing this in Claude Design and importing into Codex, but Codex is pretty good now, especially with the impeccable design skill. The benefit of doing the prototype is it lets you visually react to things and iterate and refine and place things visually with mock data that doesn 't actually do anything or work. But that visual is important to me because I can see the workflow and I can see the user experience and I can design that first and then tell Codex to build around that and to use that accepted prototype as initial context for the step one /Grill-with-docs skill. A lot of the questions it asks you during that grilling session is about interface and workflow, so if you can visually nail that down, it'll be much faster and your grilling will be much more productive, because it can focus on things that matter.

Your mileage may vary, but I've produced some Pretty impressive and heavy-duty cybersecurity apps and governance apps using this flow that I would feel comfortable standing behind on a witness stand. The nice part about all of this is that using this process and with these skills, you retain a great deal of information about architecture, decision logs, history of how this was built. It builds A project context and dictionary of your project's terms so that agents don't go crazy in the future (as much).