How to Stop Opus 5's Jargon and Wall-of-Text Problem
Two five-minute configuration changes, a custom output style and an on-demand skill, turn Opus 5's dense jargon and wall-of-text replies into plain, scannable answers.
Opus 5's jargon-heavy, wall-of-text replies are a configuration problem, not a smarter-model problem, and get fixed with a custom output style plus a small on-demand skill that shortens answers when you need it.
Who This Is For
Read if. Skip if.
READ IF YOU ARE…
You use Claude Code or Opus 5 regularly and find its answers too technical or too long to skim.
You want a copy-pasteable fix you can apply to your own Claude Code setup in under ten minutes.
You're curious how output styles differ from CLAUDE.md for controlling an agent's default voice and behavior.
SKIP IF…
You don't use Claude Code and have no interest in configuring an AI coding agent.
You want a technical explanation of why LLMs produce jargon, not a practical configuration fix.
TL;DR
The full version, fast.
Opus 5 tends to answer simple questions with dense jargon and full-blown essays, wasting reader time and tokens. Anthropic's Lydia Hallie shared the actual fix: a custom output style, set under /config, which rewrites Claude Code's core tone and (unlike CLAUDE.md, which only loads once) gets re-injected throughout a session. An ELI5-based style, optionally layered with the ASD-STE100 controlled-vocabulary standard, kills the jargon. The separate wall-of-text problem is better solved with an on-demand skill, like a one-line /probe command that restates the last answer in plain language, since some tasks genuinely need long replies. The larger point: benchmark-leading intelligence and good user experience are different things, and the fix is tuning your own output style and skills rather than waiting for a better model.
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Cold open stating the problem: Opus 5's replies are jargon-dense and overlong, plus a promise of two fixes and a free resource.
00:33 – 02:13
02 · The Jargon Problem
A CRM open-rate example shows Opus 5 defaulting to technical terms (MPP, send-time optimization, geodata) even on a plain business question.
02:13 – 03:23
03 · The Wall of Text
References Peter Levels and Niklas Grund on Claude's verbosity, then the RoboNuggets community pitch.
03:23 – 05:01
04 · Fix 1: A custom output style
Anthropic's Lydia Hallie's fix: Claude Code's output style setting under /config controls tone; demo of a custom ELI5 style.
05:01 – 05:36
05 · Adding Simplified Technical English
Layering the ASD-STE100 controlled-vocabulary standard on top of ELI5 for extra clarity.
05:36 – 06:38
06 · The one-prompt setup
A copy-pasted prompt that writes the output style file and updates settings automatically; verify by asking Claude which style is active.
06:38 – 07:55
07 · Why not just CLAUDE.md?
Output styles sit in the core system prompt and get re-injected mid-session; CLAUDE.md only loads once, at the top.
07:55 – 10:32
08 · Fix 2: A skill for length
Wall-of-text fix uses an on-demand skill instead of the output style, since some tasks need long answers; demos /probe, 'Wait What?', and a custom /quick skill.
10:32 – 12:18
09 · The bigger takeaway
Even the top-benchmarking model has UX problems; the fix is tuning your own output style and skills, not waiting for a better model.
Atomic Insights
Lines worth screenshotting.
Opus 5 defaults to more technical, more comprehensive answers than most people actually want, even on simple questions.
A wall-of-text answer costs you twice: your own reading time, and real money in output tokens.
Claude Code's output style, set under /config, controls how the model talks to you, separate from what it knows.
ELI5 works as a style instruction because these models were trained on the actual r/explainlikeimfive subreddit.
ASD-STE100, a controlled-language standard originally written for aviation maintenance manuals, restricts vocabulary enough to make AI answers noticeably clearer.
An output style lives in the core system prompt and gets re-injected as a reminder throughout a session; CLAUDE.md only loads once, at the very top.
The same brevity rule technically works if you put it in CLAUDE.md instead, it's just less durable there than in an output style.
Baking brevity into the default output style is the wrong fix, since some tasks genuinely need long, detailed answers.
A one-line skill that just restates the last message in plain language with zero jargon fixes most wall-of-text replies after the fact.
Opus 5 leads independent benchmarks for raw intelligence and still has a real user-experience problem, proof that benchmark rank and daily usability are different things.
The fix for an overly verbose model isn't waiting for a better one, it's tuning the output style and skills you already control.
Apple Mail's privacy feature pre-fetches every email image through a proxy, which is part of why email open-rate tracking has been unreliable since 2021.
Takeaway
How to stop Opus 5's jargon problem
AGENT TUNING
Opus 5's jargon-heavy, overlong replies come from a configuration problem, not a smarter-model problem, and get fixed with a custom output style plus a short on-demand skill.
02The Jargon Problem
Opus 5 defaults to a more comprehensive, more technical answer than most people actually want, even on plain business questions.
It assumes you already know field-specific jargon, so a simple question about email open rates comes back full of terms like MPP, send-time optimization, and geodata.
The jargon habit isn't obvious until you try to actually use the answer, which is when the extra decoding work becomes a real time cost.
03The Wall of Text
The problem is widespread enough that it made the rounds on X, credited to a post by Peter Levels and an article by Niklas Grund describing Claude's output as verbose and increasingly jargon dense.
A simple question routinely turns into a full essay, which costs you reading time and costs real money, since Claude bills for every output token it generates.
Long, technical answers create a cost beyond your time: more output tokens is a direct, measurable expense.
04Fix 1: A custom output style
Anthropic's own Lydia Hallie shared the actual fix: Claude Code's output style setting, found under /config, controls how Claude talks to you, separate from what it knows.
An ELI5-based output style is enough to flip the same jargon-heavy answer into one that leads with the plain-English point and explains itself as it goes.
ELI5 works as a style instruction because these models were trained on the actual r/explainlikeimfive subreddit, so the format is baked into how they respond to that exact phrasing.
05Adding Simplified Technical English
Layering ASD-STE100, an aviation and technical-writing standard that restricts vocabulary to a controlled word list, on top of ELI5 made answers noticeably easier to parse.
You don't have to copy anyone else's exact output style wording; a published standard is a starting point to adapt to your own reading preference.
06The one-prompt setup
You can hand Claude Code one copy-pasted prompt that writes the output style file into your output-styles folder and updates the relevant settings file for you, no manual editing required.
Confirm the change actually took by opening a fresh session and asking Claude directly what output style it's currently using.
07Why not just CLAUDE.md?
CLAUDE.md only loads once, at the very top of a session, so its instructions can get diluted or forgotten as the conversation runs long.
An output style is written into the core system prompt, and Claude Code re-injects reminders to follow it throughout the session, which is why it holds up more consistently.
The same rules technically work if you put them in CLAUDE.md instead, they're just less durable there than in the output style.
08Fix 2: A skill for length
Baking brevity directly into the output style is the wrong move, because some tasks, real knowledge work, real production code, genuinely need long, detailed answers.
The fix for length is an on-demand skill you invoke only when you want an answer shortened, keeping the default style untouched for when detail is actually needed.
A one-line skill like /probe, whose only job is to restate the last message in plain human language with zero jargon, is enough to fix most wall-of-text replies after the fact.
Building your own skills matters more than copying someone else's, since each person's workspace and shorthand is different.
09The bigger takeaway
Opus 5 leads independent benchmarks for raw intelligence, and still has a real UX problem, proof that benchmark rank and day-to-day usability are two different things.
The fix isn't waiting for a better model; it's tuning the 'agentic operating system' around the model, your output style and your skills, since that's what you actually control.
Expect the same jargon and wall-of-text pattern to resurface in future model versions, and expect the same two-layer fix, style for tone, skill for length, to keep working.
Glossary
Terms worth knowing.
Output style
A Claude Code setting, changed under /config, that rewrites the model's default tone and voice for every reply. It sits in the core system prompt, separate from what the model knows.
CLAUDE.md
A markdown file loaded once at the start of a Claude Code session to set persistent instructions and project context. Unlike an output style, it isn't re-injected as the session runs long.
ASD-STE100 (Simplified Technical English)
A controlled-language standard, originally written for aviation maintenance manuals, that restricts vocabulary to a smaller, unambiguous word list to reduce jargon and ambiguity.
ELI5
Short for 'explain like I'm 5,' a style of answer that avoids jargon and explains concepts in the simplest possible terms.
Skill (Claude Code)
A short, reusable instruction invoked on demand, like a slash command, that changes how Claude handles one specific request without changing its default behavior.
MPP (Mail Privacy Protection)
An Apple Mail feature that pre-fetches every email image through a proxy server, which makes email open-rate tracking unreliable for a large share of recipients.
Resources
Things they pointed at.
00:03linkRoboNuggets free jargon-fixer PDF resource
03:00productRoboNuggets Claude Living Masterclass + Agents as a Service course
03:33linkLydia Hallie's post on Claude Code output styles
02:30linkPeter Levels' post on AI wall-of-text jargon
“It seems to always default to being more comprehensive and more technical than most people would probably want it to.”
names the core problem in one line→ TikTok hook↗ Tweet quote
02:30
“Reading AI output today is extra effort. It's verbose, it frequently contains all too plausible nonsense, and is increasingly jargon dense.”
sharp, quotable diagnosis of the problem→ IG reel cold open↗ Tweet quote
03:34
“The output style is simply just that. It is the style by which Claude Code provides its output to you, or how it talks to you.”
clean definition of the key concept→ newsletter pull-quote↗ Tweet quote
07:00
“It becomes part of the core system prompt, and throughout your session Claude Code actually gets reminded about this rule so that it follows it more consistently and religiously.”
explains why the fix actually works→ newsletter pull-quote↗ Tweet quote
10:55
“Even though benchmarks show the raw intelligence of these models, user experience can sometimes differ.”
the video's larger thesis in one line→ TikTok hook↗ Tweet quote
The Script
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analogy
There's a widespread problem plaguing Claude users recently, specifically on Opus five because its replies tend to be confusingly long, packed with all too possible nonsense, and it's becoming more and more jargon dense. The good news is that Entropic already shared the fix for this.
It's super easy, and the principle behind it makes your setup faster and cheaper, and it lets you finally understand what the heck your agents are actually saying. And by the end, I'll hand you a resource that solves all of this automatically just by sending it to Claude.
Let's dive into it. So if you've been using Opus five heavily the past few days, you may have noticed two specific problems with it. The first one's the jargon problem, which is its tendency to use technical terms or acronyms much more versus earlier models, which makes it much harder to understand and work with.
Just to give you one simple example, and this is probably not the worst of it. If you ask a simple question to Opus five like this, where I said our CRM dashboard says open rate is 32% and I said from a conversation with a peer, we discussed how open rates are basically fake now. So I asked it what does that mean and should I care?
It did give us a proper explanation here, but it seems to always default to being more comprehensive and more technical than most people would probably want it to. And you can see its tendency to assume that you know every single jargon in the field as well. Like for example, here it's saying every Apple mail recipient with MPP on registers as an open.
And it also tends to use a lot of technical jargon like send time optimization, geodata, or device data derived from opens. MPP masks IP and reports a generic device, so all of this is corrupted.
So you can see what I mean. Right? And like I said, that example was probably not the worst of it because I first became aware that this is sort of a widespread problem when I saw this tweet by Peter Levels who's pretty popular in the in the hacking space where he shared this snippet of an article that made the rounds around x recently.
And I can probably show the actual article just to give credit where it's due. So this was written by Niklas Grund, if I'm pronouncing it correctly. And I think he summarized the problem really well here where he's saying that reading AI output today is extra effort.
You can pretty much do it, but it is extra effort. It's verbose. It frequently contains all too plausible nonsense and is increasingly jargon dense.
And then he says that he recently got this sentence from Claude that even I don't know what this means really. And that the second but related problem is the wall of text issue. So if we go back to our example here, you probably experienced the same thing where you ask it a simple question and then it goes into a full blown essay and gives you a wall of text as an answer.
And for most cases, there's multiple issues with that. Right? Because it wastes your time because you need to understand and read through this whole thing in order to get to the point.
And secondly, there is also a corresponding cost for tokens because the longer it's output to you, the more tokens that Claude is consuming. And so if you have this same problem with Opus five as well, which a lot of people seem to be using as their default, then you're in the right place because today I'll be showing you the two solutions for those two unique problems.
And by the way, if you want to learn how to build and sell AI systems that businesses actually pay for, then that's pretty much all we do over at the Robo Nuggets community, where not only do you get access to the Cloud Living Masterclass, which we update every week and takes you from zero to mastery with the latest on AI, but you also get access to our agents as a service course, which walks you through how to actually get paid for all these AI skills that you are learning.
You also get to be part of a genuinely great community of AI builders. In fact, you can see just some of the recent wins our members are getting from the program right here. So if you want to start earning from AI, then check that just in the pinned comment below.
Now back to the video. So let's start with the jargon problem. And the good news about this is that Entropic's team actually talked about how to fix this one issue.
And that fix is courtesy of Lydia who's a member of technical staff at Entropic. And essentially, it all has to do with this configuration in Cloud Code that's called the output style. And the output style is simply just that.
It is the style by which Cloud Code provides its output to you or how it talks to you. And I'll just show you where to find it, at least in the terminal view, but I'll show how to do it in the desktop app as well if in case you're more comfortable there. But here in the terminal, if you have cloud code open, you can slash config, which brings up all your settings.
And if you find output style here, and if I click on enter, what you would most likely find is that your cloud is set to the default output style, which is that verbose jargony output that OPUS five usually defaults to. You have other options here like proactive, explanatory, and learning that Claude code ships with by default.
But you can see that I have a fifth one here that I added as a custom called e l I five. And this e l I five is the fix that Lydia was talking about here.
And in case you're curious, e l I five simply stands for explain like m five. It is a popular subreddit, and so the reason why that acronym works for a lot of models, including Opus five, is because they've been trained with the entirety of the Internet including that subreddit. If you're curious, this is what that subreddit is and there's like thousands of posts in here asking questions in the ELI five format.
And you can be sure that these models have scraped this whole thing in order to understand how people respond to these questions. But the core principle of it is if you want things to be simple to understand, then this ELI five is one way to do it.
Now, obviously, you don't have to adopt the exact verbiage that Lydia has here. For example, one thing that I added in my output style personally is this tip from Andrew that I found where he asked Claude to only report to him in this ASD s t e 100 simplified technical English. So what is that?
Well, in a nutshell, that's essentially a controlled language standard that uses a more restricted dictionary. So a list of words that are much easier to understand. So it avoids jargon.
It avoids a lot of those technical vagueness. And at least from what I found personally and for a lot of people, it seems that standard seems to help a lot in terms of just making talking to your agents much easier and much more seamless. So how do you now apply this fix and actually change your output style so you can test it out?
Well, what you can do is just copy this prompt or take a screenshot of it and send it to your Cloud Code. And what you're saying here is simply to set your output style to the one below, which is this whole snippet from Lydia with that addition of the ASD SDE 100. And then the important part here is the direction to save it in your output styles folder, which obviously depending on your workspace, the location of that folder may be different.
But the good news is Cloud Code can probably find that for you. At least for me, this is where it put that markdown file. And within this markdown file is just this piece of text.
And then the second thing that this prompt will do is to just set this output style for e l I five in the appropriate settings files. And you can see for me, because I already have it set, that is what Claude also told me where it created that style file for me that eli5.md, and it also updated the relevant settings.
And the best way for you to check is to just open up a new session and ask what output style it's using now just to confirm. And if you need to make any changes to it, then you can just tell that to Claude and it will update this output style for you. Now you may be asking why it's important to put these rules in the output style instead of something like the Claude dot m d.
And the truth of the matter is that you can actually put these rules into Claude dot m d, but it just isn't as effective. And if you're curious, it has to do with two things. One is the strength of the placement with regard to the output style.
Because if you notice, what we changed earlier is the actual settings for Cloud Code. So it's written into the core system prompt of your Cloud Code instance. And then more importantly, at least I would think, is that under the hood, what Cloud Code actually does is it auto injects these sort of nudges, these reminders like stick to your output style even midway throughout your session.
So if you were to show that visually, your Cloud. Md, that does get preloaded into every session that you start but only at the top. Right?
But the great thing about putting this rule into your output style is that it becomes part of the core system prompt, number one. And number two, throughout your session, Cloud Code actually gets reminded about this rule so that it follows it more consistently and religiously. And just to give an example of that same question that we ask it, if you read through this, it's much more legible now, at least in my view.
It leads with the key answer where it's saying that that open rate is not all real people, and then it tells the clear story here of why that is and then ends with this conclusion that anyone can understand. Now that fixes the jargon problem. Now let's go to the second issue, which is this wall of text that you usually get from Opus five.
And for a lot of use cases, especially knowledge work or production code, the tricky part about this problem is that you do sometimes need long pieces of text in order to get a lot of the detail that you need. And so this is why generally, I won't advise people to put the wall of text fix right in the output style. And so what I would generally recommend is to just use a skill when you need that wall of text to be shorter.
And in our community, I always advise people to make their own skills because each of our work is different. But let me give you some ideas and I'll also share how I do it personally. One really interesting skill that I found is this one called slash probe.
It's probably one of the shortest but really useful skill that you can add to your arsenal because it is only one line. So its sole purpose whenever you invoke it is for your agent to restate the last message in plain human language with zero jargon. So if we go back to this wall of text, and you can see here I just used that skill slash bro, when it rewrote their response, it's saying here, okay.
So basically that 32% never meant 32 out of a 100 people actually read this, and here's how it actually works. So I'm not going to read the whole response here, but you can see just how much more understandable and better it is versus what we started. Right?
Another example of a skill that I found is this one from Matt Poka. It's called Wait What? So again, it's a very short skill.
It says, don't understand where you've got to here. Repitch that and give a little bit of context. And this is what I'm saying where you need to create your own skills because you can see from Matt's workspace here, he probably has this context dot m d that he uses a lot.
You may not have that. So what you can do is to take a screenshot of this or copy this skill and just ask Clog to personalize it for your own setup. Now what I tend to do personally in conjunction with slash bro, since you can see sometimes Opus five still defaults to a wall of text if it doesn't know how long you want the response to be, is I use this skill of mine called slash quick where I just declare a number, in this case three, and it gives me just three points in sequence of what it thinks is the most important takeaway from that whole essay that it wrote.
And just to show you what that skill looks like, I think it's this one. Yeah. So you can see this is the slash quick skill.
And you can see just in its current state, it just has rules on when to use it, when I don't declare a number, when I declare a number. And apparently, there's now, how many, two modes here that probably naturally arose since I use this skill a lot and I also ask Claude to tweak it depending on our conversation.
But that is one idea by which you can cut that wall of text into more bite sized chunks. But like I mentioned, it's probably better for you to just get these ideas for skills and create them yourself as well depending on your type of work. Now what I talked about just now are pretty simple fixes, but if you take a step back, there's actually a larger takeaway to this whole thing.
Because interestingly, and if you remember, Opus five is actually the best in terms of a lot of benchmarks that we see online, including this one from artificialanalysis.ai where it is leading at the moment. And so the first key takeaway here is that even though benchmarks show the raw intelligence of these models, user experience can sometimes differ.
So it's sort of like if you bought a computer with the highest specs available, but then you actually find that you prefer your older computer just because of maybe some unique features that that old model have. So it's quite similar to AI models also is what I'm finding. And so what you should realize here is that, let's say, a year or two down the line where you have OPUS seven or OPUS 10 already, if those feature more powerful models have the same issue as well.
The good news about it is that these AI models are very malleable and you can just tweak your AgenTeq operating system or essentially the way that you talk to these agents through these same solutions that we talked about and that will just provide a much better experience for you when you work with AgenTeq AI. And so just remember that you can always direct these models with your preferred output style as well as these skills which are essentially shortcuts.
And just to make it easy, everything that I talked about in this lesson in this video, I just put it all in this eight page PDF which you can probably just send to your Cloud Code and just pick out the prompts and the styles and the skills that you would need and just tweak them to whatever your workspace needs. So you can just find this whole thing down in the description.
I hope that was helpful. And as always, appreciate you for making it until the end because that helps me a lot. I'll see you next time.
Thanks.
The Hook
The bait, then the rug-pull.
Opus 5 answers with jargon and walls of text, and Anthropic's own team already shared the fix. Two configuration changes, an output style and a couple of on-demand skills, are enough to make it plainspoken again.
Frameworks
Named ideas worth stealing.
03:23model
Two-layer fix: output style + skill
Output style — sets the default tone and voice for every reply, baked into the core system prompt
Skill — an on-demand shortcut you invoke only when you specifically want a shorter answer
Jargon and length are two different problems that need two different fixes: a persistent style change for tone, and an on-demand skill for length, since some answers genuinely need to be long.
Steal forany AI agent workflow where default tone and on-demand brevity need separate controls
05:01concept
ASD-STE100 (Simplified Technical English)
A controlled-language standard built for aviation maintenance manuals, using a restricted, unambiguous vocabulary. Adding it to an output style noticeably reduces jargon and vagueness in AI replies.
Steal forany output style or system prompt where you want measurably plainer language
CTA Breakdown
How they asked for the click.
VERBAL ASK
03:00product
“check that just in the pinned comment below”
brief mid-video pivot to the RoboNuggets community pitch (masterclass + agents-as-a-service course), then an explicit "back to the video" cut straight back to the tutorial
FROM THE DESCRIPTION
PRIMARY CTAWhere the creator wants you to go next.
A three-line prompt that fans Claude out into paired builder and critic sub-agents until every piece clears a stated quality bar — and the one condition that decides whether it helps or hurts.
A creator has Claude design a visual second-brain system for his own workspace, then proves it answers questions faster and 40% cheaper than a default session.
Same one-shot prompts, two models, three real builds — a website, an app clone, and a 3D game — scored on intelligence, cost, and time, not just vibes.
A walkthrough of routing Claude Code through a ChatGPT subscription's GPT-5.6 Sol model, plus a two-model skill that has Claude plan while Sol builds, for roughly a quarter to a half less per task.
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