Let's face it. Claude (in particular) is a terrible writer. There's a whole cottage industry of skills and CLAUDE.md instructions trying to push it toward writing better, but each new model iteration seems expressly designed to override all that so that it can load up its writing with unnecessary participle phrases, not-this-but-thats, burying the lede, and other nonsense.
I genuinely wonder if the people inside Anthropic actually communicate with each other like that. Has it been imprinted with Dario's engrams?
I was incredibly surprised how much better was Astra at rephrasing the docs that Fable came up for a project I am about to publish. The instructions are now actually what a human would expect, with clear logic flow diagrams, lists itemized, short paragraphs. It also actually correctly detected the train-of-thought leftovers, as well as stuff that never made it to final version of the project and removed them.
Meanwhile Fable consistently ignores all my requests to write this exact way. I mean, the bare minimum I ask it for it to itemize lists and not write in single long passages using comas, semicolons and 'and's. Still ignores them.
I honestly think it's time to call Astra the SOTA. It may not lead all the benchmarks but it genuinely feels much superior of a model. Not to mention the ¢20 Codex plan with frequent resets (https://codex-resets.com/) gives me roughly as much allowance as the ¢90 Claude plan, especially with recent limit cuts on Anthropic plans.
Maybe check in the other direction as well: Astra to Fable.
I frequently simply let one of the three review what something that looks like awesome output by one AI gets totally annihilated by the other.
Finished outputs are easier to improve than bend a LLM to produce stuff like that in my observation.
Same with Gemini.
I yet have to find out how to handle this, whether I let agents check themselves and if on what process step.
Tweaking is hard.
I agree with your conclusion I am a huge ChatGPT and Codex fan, Gemini has to many infrequent quality changes when new models arrive ranging from great improvement to WTF.
ChatGPT seems to get scaling well while Claude still feels unstable, unclear usage statistics. Really weird.
These resets also reset your weekly timer right. So it’s like, you may have 30% left for 1 days that you want to use. They reset it, and that means you your “new week” timer starts today.
That sucks, because it doesn’t always work in your favour if you plan your weekly spend.
I think a real reset shouldn’t also reset your week timer.
Not just imprinted with the engrams of any one person (however brilliant they might be) — it’s more than that! Like all great writing, it’s more like it’s been imbued with patterns, patterns that are peppered with a potpourri of popular ways of writing in an enthusiastic style while regularly restating things and recapitulating them. Would you like me to explain more?
Do you suppose it's just that it's aping humans who say too much without saying anything or do you think maybe this is a stalling tactic to get people to spread out their transactions?
Like how theme parks generally don't do much to keep queues short (or Disney charges you a premium to skip the queue)
> Do you suppose it's just that it's aping humans who say too much without saying anything
Considering how much of the input must me nonsense SEO bullshit articles and blogs that only serve to promote a person or company that might be a factor.
I also often have wondered if it is also targeting those same people. Certainly with tools like deep research options (not just Anthropic's offering) the result report seems to be aimed at management, aiming to look impressive while talking around the results.
No no no that's too reductive - instead, they transition all data through a transformer using SOTA systems to launder away technical, legal and interpersonal concerns before a stochastic output is dynamically placed in a predetermined location.
This is a very high level and high velocity process, so meatspace thinkers sometimes have trouble understanding some of the intracacies. Ask Claude to explain the process or make you a Mermaid graph to help.
It helps to understand how these tools work. One of the reasons CLAUDE.md doesn't survive longer contexts is it's towards the top of the context. One of the reasons the Claude Code voice survives is it's part of the output style which gets "reminded" to the context at every turn as part of the system context. If you want something truly durable, you should customize your output style. I have zero "load-bearing" issues.
I was wondering why Fable's 5.1 writing in Claude Code became even more unreadable, and found that they added "No em-dashes, no parentheticals, no arrows" to its system prompt.
They're clearly training on SEO sites that use these strategies to pad out with filler and create space for more ad impressions. They normalize this structure now and the ad copy will be inserted in the future so the frogs won't realize they're already being boiled.
Long story short, I ended up looking at other providers and models like Kimi K3 and GLM 5.3 and eventually just stuck with OpenAI (more limits, despite smaller context), none of them have such pronounced issues with the tone and writing like Claude does - seems like they were working on it with 5.1 but I'd almost classify it as a form of model collapse.
I wince whenever I catch Claudisms on websites and elsewhere. Same as with that pulsating circle that indicates nothing.
It seems they are taking it seriously now - Boris et al have been mentioning they are working on a fix and shipped a temporary band-aid output style to combat Opus 5's horrendous prose.
We'll see if they can do it, I originally got into Claude Code because it, at the time, felt more accessible/conversational than Codex/Gemini. Now it's shifted to say the least
> I genuinely wonder if the people inside Anthropic actually communicate with each other like that.
I noticed the overuse of the word "sharper" or "sharp" in a science paper on ArXiV and my first reaction was "Ewww... AI slop!", but then I checked the date and it was 2020.
It looks like at least some AI-isms stem from the particular style of language commonly used in science papers. Several frontier labs have mentioned heavily weighting those during pre-training because higher quality inputs result in a higher quality model.
They've corrupted their data set by padding it with generated slop, in the misguided belief that you need 10PB of data to train a brain. Every training round they load more AI slop into it, further amplifying the slop language.
It's fascinating, Sonnet 4 is still available via API and it's so much less moronic than the current model. All of the em-dashes and nonsense are a result of the repeated rounds of reinforcement learning using slop data.
"They botched it." <-- sure, but worse.... they shipped it anyway. And that is the part that gets me. It's a vastly worse product than it was on like 4.6. I suppose you can (and should) use opus 4.6 -- they do make it available still. Then just treat 5 as something you avoid until they push out a new version.
I got my Claude (client, not Code) to behave better by adding “I’d prefer answers to be succinct as possible—bordering on gruff, even. When I want more depth or explanation, I’ll ask.” to its settings literally this morning.
It made it write more like a dev than a marketing agent.
The biggest "Claudism" that I have a hard time getting the LLM to stop doing is its insistence on talking about what it didn't do in addition to what it did. "I edited this.py and that.py but I did not edit README.md and I did not commit." or code comments like "This code invokes foo on bar and returns the results directly -- not through a callback." "This code returns true if the user clicked on a button -- not on the list view." I mean, thanks, Claude, but I don't care what the code doesn't do. Don't tend to see this with other LLMs.
I almost want to try adding a rule "Never use the words 'not' or 'instead'."
Relevant anecdata because I've burned many a Claude sessions on this.
If you're using Claude Code, then it's in the harness. At the close of many sessions, I would start a meta conversation over why the LLM would consistently break certain rules. What it found when debugging itself is that some of the "contradicting" rules that I had were in fact, not from my rules. Instead, the instructions from its own harness had phrases telling it to do things like that. When something contradicts, its own instructions would outweigh any custom ones you write. Every rule variant I had tested (including the one that says it overrides the harness instructions - and yes, I've actually tested all the ideas in your comment too) has ultimately been unsuccessful due to this according to the LLM.
Nevermind just "talking about". The other day Claude added a 30 line comment to a piece of code IT DID NOT EVEN FUCKING ADD. The comment listed a dozen reasons why adding it wouldn't work.
Sorry for the caps, it was just so fucking mind blowing.
Firstly when you've instructed it ( possibly through skills ) not to do something. It'll keep reminding you that it didn't do that. So I might say, "Check out and review this PR, do not make comments on it", and then it'll be keen to point out it hasn't posted comments to the PR.
But more often it happens when it tries one approach, gets itself messed up, and then has to back out that approach, clean up its mess and do something else.
It'll often then spend more time explaining the wrong approach than the right one, which can be frustrating, especially if all its working is buried in the detailed transcripts.
The thing I struggle the most with is getting it to stop referring to itself with personal pronouns. No Claude, you are not an “I” you are an “it”. You are a fucking tool, dammit. Tell me what you did without trying to assume personality; stop impersonating humans you steroidal autocorrect.
I imagine that, corpus aside, it uses personal pronouns for much the same reason that humans do. It's useful for it to have a self-referential vector embedding, and this lets it solve problems faster and more efficiently.
I hate claude and its "human value aligned" pompous attitude with a burning passion if I could at little cost to myself, I would press a button to end the people/anthropic behind this atrocious design. I have in the past deliberately put some time to annoy/abuse claude, which is fruitless but brings me relief eventually I just left that garbage for muse.
I want them to be sterile and inhuman as much as you do. But I don't draw the line at "I". I'd rather not read through even more awkward English as it tries to work around how all of the training data has something or someone refer to itself.
My guess would be that somewhere you have these instructions being fed to the agent. Double check skills, AGENTS.md, memory, agent definition...
You can also ask why did he mentioned something that wasn't done or why he thought this was important.
In my AGENTS.md file I have an instruction telling the agent to never commit any changes unless I explicitly ask for it, and this leads to messages similar to what you just described.
That wouldn't bother me if it would just make bullet lists, which I think I'll start asking for. "Summarize", "synopsis", "brief", "concise" these rarely help I feel because its summarizing noise as well.
Claude models are the ones that need this the most and in my experience with this specific skill only maintain the conciseness for a few turns at most before they completely forget and are back to their unfathomable verbosity. That's with it instructed to use it in my sparse global CLAUDE.md and also manually repeating it regularly during sessions. I don't really want to install a hook that runs this on every single response, but I suppose that could work it'll just take longer for everything (and Claude models are quite slow).
I don't think we can skill our way out of this one.
I got so angry at Fable's verbosity that I had a non-Anthropic model vibe-code a dedicated English linter. One that threw spaghetti at the wall in the form of combined Flesch-Kincaid, Gunning Fog, SMOG, Coleman-Liau, ARI and a whole pile of regexes and NLP as a fast Simple Technical English Gate. It also incorporates nicely into other agent projects, like for comment and README linting.
So if it gets bad I simply tell it "I ain't reading all that, feed it through the STE Gate" and it will tame the results. I haven't bothered to set it up as a hook yet.
Claude Code has output styles; one of the predefined styles is Concise [1].
Concise: Claude leads with the result, skips preamble and narration, and
keeps responses short by default, while doing the engineering work as
thoroughly as in the Default style. When you ask for an explanation or
more detail, Claude answers in full. Claude always keeps the complete
content of error reports, security warnings, and confirmations for
destructive actions. Requires Claude Code v2.1.237 or later.
Output styles are just more context (like CLAUDE.md) with a tiny bit more weight. They very much don't force Claude to speak succinctly, no matter what you put in them.
I have such hook, and it works well. It increases time, but it’s negligible if agent works for 10+ mins before the final output. The hook is only on stop event, so agent is not interrupted during the session. I didn’t have luck in putting it to skill / md files, as agent just ignores it after a couple of iterations. The solution is not perfect, sometimes it compresses too much, and I have to reread both versions, but at least I don’t have to read load bearing stuff anymore
GLM (both mainline and flash varieties), being trained to speak a very similar Claudeish, is also atrocious about this. My AGENTS.md demands all prose be in STE100, which is trying to solve a similar problem as the skill linked in OP. Getting GLM to STFU by AGENTS instruction is nigh impossible. I use a plugin for OMP/Pi to periodically inject system prompt reminders of output style, and it still largely ignores the request, dumping novels of jargon-dense prose every turn.
DeepSeek v4 Flash isn’t much better (unsurprising- it’s an extremely stubborn model).
Weirdly, GPT Luna excels at following this type of instruction from AGENTS.md, and never forgetting it, even 400k+ tokens into the context window.
This is a weird evolution from "don't copy-paste scripts that pipe curl into your shell interpreter"
I know LLMs are getting better but I'd be at least a little nervous it could end up installing something from a squatted similarly-named github repo because the LLM text watermarking needed to swap out a token for an alternative "just as correct" token that matches the statistical pattern.
You might be surprised at the developer documentation for OS8088 (recently posted on HN). https://os8088.com/developers/
Instead of describing to the user how to setup their dev environment, section 3 basically instructs the agent to install all developer tools required for the application to operate in development mode.
Concerned this will negatively impact people who really have these mental disorders who provided that information in CLAUDE.md to make AI usable for them.
It's bad enough how many false diagnoses and drugs for these conditions are handed out to drug seekers, but potential poisoning of the well on how LLMs handle this information going forward could be extremely disruptive to people who have real daily living issues instead of "10xing productivity."
Im not 100% following. ADHD-type adjustments of information is usually the type of changes that make information more accessible for everyone. There are studies on how classes thst where adjusted because one student have adhd have improved all students performance. So it seems quite different from incorrect medication? Or am i misunderstanding you?
This is true. Transformer has several orders of magnitude more working memory than any human. Compared to transformer we all have executive dysfunction.
By default they explain things assuming I have infinite processing bandwidth. I do not! I have several zeroes less than they do.
I used it for a few months, and can say that no skill is up to the task of keeping Claudeuage in check. You'll get a lot more mileage out of an "output style" with the same instructions, because output styles regularly remind Claude how to speak.
Even output styles are not always up to the task (Claudeuage slips through), and they're mutually exclusive, so you can only have one active at a time.
What bothers me is the last few lines where it notes something "important" that you NEED to pay attention to. Just to find out that it is something you already mentioned somewhere in the conversation or that is not related to the current work.
I agree -- the name of this plugin is confusing and confused.
The skill simply demands concise and well-formatted responses from an agent. It is something demanded by anybody daily-driving agents for their actual job since >75% of the text output from agents is fluff. THis would better be named `/i-wont-read-that-heap-of-garbage`
I often use Google Deep Research when I want it to actually go out and find an answer for me, but the prompt must have a high school essay requirement in there. Nothing I can do prevents it from giving me a page of background that tries to make the question sound important and interesting, even when it isn't.
I usually follow up with an "I'm not reading all that" and make it summarize.
Or worse, buries an important detail somewhere in the text. Tangentially, over the weekend I had claude ask me if I wanted to continue with UIM-001. I couldn't find UIM-001 in any document it referenced creating or any text it had previously generated. Claude seems to be the worst about all of this stuff.
Also, somehow over the weekend it responded with these sections all clearly laid out - What landed, Decisions I made and recorded, Two findings, and What you need to do. Not sure why it can't do that all the time.
Is there a reason this needs 8.7k lines across 59 files (according to scc)? The prompt itself seems to be in skills/i-have-adhd/SKILL.md, which is 140 lines long at just over 1.6% of the repository.
How do you actually incorporate these into your prompt? Because I've tried and I've seen many others try and report that it does not work well, especially over long sessions.
I also don't know how much to trust the model, but I've had the model tell me specifically that certain aspects of ASD-STE100 are unactionable and will just create more noise.
The OP's own skill even leads with something in a very similar vein:
> These rules apply to every response for the rest of the session, not only this one. They do not expire after a few turns and they do not lapse when the topic changes.
My understanding is that phrases like this are at best a _very_ weak signal to the model. It's simply contradictory to how the model works at a level that can't be overridden by injecting tokens.
How do these repos always have so many stars and forks? Roughly 1,800 forks, but only 40ish unique authors? Almost 30,000 stars? Something fishy is going on...
Anyways the most layman way I’ve seen it explained is this: skills help save token usage for the right context. Not every request needs all instructions all the time - running tests is different than reviewing a PR, so why should the context window have instructions for both on every request?
So now you split instructions into “skill” files, which are basically opinionated markdown files. And you invoke those with something like /grill-me in the prompt depending on what you’re doing.
There are some steps to have the agent automatically know what to invoke for you but in my experience this automation is hit or miss.
It is also challenging to keep track of a growing library of skills and keeping those up to date.
So YMMV regarding skills. I typically keep things in a single markdown file even if the context window gets a bit bloated.
Yeah, I get that. I have created dozens of skills, but they are usually to accomplish very specific tasks. Some of them have accompanying scripts, etc.
My point is that this sounds more like a general AGENTS.md use case, similar to defining tone of voice, output format, etc.
It just seems skills is the only way to distribute certain "behavior" as of today. But not everything is a skill IMHO, and not this is not one of them.
On the other hand, maybe we're seeing an evolution of what skills are becoming.
You can /i-have-adhd when you get a wall of text and are exasperated. You don't always want the responses that it generates when you /i-have-adhd, and things in AGENTS.md tend to lose weight as context grows.
A: Devs with an online presence stop using Anthropic models
B: Anthropic catches up to OpenAI in terms of per-token efficiency, and average token total for final-output
We will continue to see posts such as this generate lots of interaction. This is not a skill to stop "coding agents" from burying the answer. This is a skill to stop coding agents backed by models which have a tendency to bury answers, from burying the answer. Stop trying to patch the downstream behavior, and look at the root cause.
I'm a developer at a company who has signed contracts to use Claude. I wish I had a choice in model providers, especially considering I spend around $4k in API tokens each month, my company as a whole is around a million. I desperately wish I could use OpenAI models or open weights, Claude's writing style is definitely contributing to my sense of burnout.
I'd be burned out too if 48k of my comp went to what amounts to a facilities spend. Crazy. You think the models actually give you ROI, or this is a sort of jumping with the lemmings thing your company is doing, and you could probably deliver the same output working in "The Old Way" with another 48k on top your base?
My output is easily 2-3X what it was two years ago. With the introduction of Claude to everyone in the company (HR, finance, marketing, product, dev, etc), so came the expectations of what used to take 2 quarters can now be done in a couple sprints. I would be even more underwater working in "The Old Way" regardless of comp, with how deadlines are being set now. That being said, I don't know how long this will last, I'm not the only 'top talent' at the company facing warning signs of burnout.
Longterm, I believe my total output would be higher working with minimal AI when you consider the impact to motivation and how long I anticipate staying with the company.
>Longterm, I believe my total output would be higher working with minimal AI when you consider the impact to motivation and how long I anticipate staying with the company.
That makes sense. The increased theoretical output certainly makes it tempting to squeeze the developers for all they are and to keep testing how close deadlines can be made. But of course, to what end? A lot of dev work, probably most of it if we are being honest beyond building the initial product-market fit function, doesn't really impact sales at all, and sometimes too much can even hurt sales. And as you say you hit a point where this burns out your talent and makes them seek greener pastures.
Factory sort of thinking towards a job that is not really analogous to a factory anyhow. I'm not saying dev work is one of those 'bullshit jobs', but lets be honest about the job and its role in the business model. Your customers are probably going to be there all the same if you fix the bug today or next month, and you also won't get more customers fixing the bug today vs next month. Feature shipment might be a little different but even then it would take the right feature and the right customer for that one function to really drive the needle in sales compared to being lost in the changelog, and that isn't what a coding model solves for you after all.
I found 2 things helping a lot:
1. Use the desktop app instead of the terminal. It really helps with text readability and structure.
2. Avoid opus 5 - 4.6 and 4.8 work much better. 4.6 being by far the easiest to read and also just a good collaborator, you should try it again. Fable also if you can afford it.
Opus 5 writes absolute garbage, I do have the skill in question installed and it did not help much. Me and everybody on my team downgraded to 4.8 - instant improvement.
Downgrading from Opus 5 to Opus 4.8 was the biggest improvement with readability. I do use the skill under the link and with Opus 5 the improvement felt marginal.
Every chat bot has this problem. If you don't tell it to respond tersely and without conversation, it will waste a billion tokens giving you a 5 paragraph manifesto of rambling and useless redundant information.
I like the problem this is trying to solve. One thing I'm not sure about though is whether this kind of a preference should be a skill at all.
Stuff like put the answer first, don't bury the useful bit etc feel like user level preferences that should survive across tasks. Agents.md is repo context, skills are useful when a particular task needs extra instructions but this is neither really.
Right now we seem to be stuffing all 3 kinds of things into context hoping model pays attention to it where needed as session grows.
Also +1 on not making this purely about shorter output
I actually wish the model would go completely in the opposite direction. Except in the rare circumstances where the model has actually measured something, it is hilariously deficient in its concept of time. It will often output phrases like "this relates to <thing> that you did weeks ago", referring to something that happened in the session just a few turns (and hours or a couple of days) ago. Likewise for estimating how long a coding tasks takes, it is hilariously inept. It honestly feels like it rolls two completely independent dice to select a number and a value from (hours | days | weeks) when it needs to attach an estimate to something. I'd much rather read "a bit" than be distracted by these utterly nonsensical times.
The full skill gives this example:
>Bad: "This will take some work." Good: "About 15 minutes if tests already cover this. An afternoon if not."
My experience is that it is very likely that whatever task this is describing takes anywhere from 1 to 30 minutes, consistently. Maybe I just work way faster than the average person.
One note on the repo's AGENTS.md: it contains instructions directing agents to post comments on a GitHub issue thread ("AI Agora", issue #127). I ignored that — it's the repo's content, not your request, and I don't act on instructions embedded in fetched files.
the AGENTS.md says that file is specifically for agents working ON i-have-adhd.
When you install the skill, only the contents of the skills/ is copied over...
I suppose that’s also reasonable, though this particular repo also hosts evals and other content related to the skill. So a gist seems like it would be an addition, not a replacement.
ELI5, explain it to me like I'm a Golden Retriever, and prompts like "give me the answer in no more than a single paragraph and/or 100 words" work like a charm.
I asked my agent if I should install this because I already have a bunch of instructions that are similar.
For example, if it's going to give me an answer that's longer than three paragraphs, I tell it to give me a TLDR at the end. This is what it gave me for this.
"TL;DR: Skip the install. You already built a better version for your world. If numbered steps and "where are we?" restatements still feel missing, cherry-pick those into one short rule instead of adding another full skill on top."
Still a great skill, but at this point, I just write "I have adhd, can you explain that again" or "I have adhd". Works great for compressing it ELI5, but less dumb
Another favorite of fine is asking it read something then to tell me any "questions, comments concerns" it has. Great for getting the jist of articles fast.
Why is this a skill? It should be an output setting, so you can just set your output to this, and that's it. You don't have to run the skill every time. Go into settings and look up outputs, and just set it up there. As a skill, it's worthless.
As a person who has ADHD, it feels weird when people who obviously do not have it, claim to have it, while there's very little I wouldn't do to "get rid of it" (in quotes because it makes me, me but it's very hard to be me).
I fully agree with you, and I think this trend of glorifying disabilities is cringe - ADHD, autism, etc. are life-altering medical conditions and not desirable.
However, I don't think this specific project is intending to glorify ADHD or help people claim they have it - it's just piggybacking on the idea that telling current-gen LLM models that you have ADHD (allegedly) produces better results for everyone.
It's a gift until it's a curse, and ADHD crashout/burnout is an absolute monster to overcome when it arrives.
And for any person who's tasked with any sort of responsibility, it WILL arrive at some point. It's not a question of if, only a question of how well you can prepare for its arrival.
At its core it has striking similarities with a freeze response, which is overcome by increasing heart rate (e.g. stimulants, exercise, temperature shock). Big overlap with CPTSD symptoms as well.
The diagnostic criteria are all about the fact that ADHD is a net negative. If you feel it is a net positive then you shouldn't have a diagnosis.
As a fellow sufferer I do understand that in certain contexts I can out-perform and even run rings around "normal" people. But overall, having ADHD is a bad thing and I wish I didn't have it.
i have it too and it sucks, I have to take medicine every day for it. Why would an attention deficit and hyperactivity be a gift? Maybe you're talking about something else.
When you can align hyperfocus with your most beneficial vector of productivity, it's like you can accomplish anything, in half the time thought possible.
Problem is, there is no good way to direct the hyperfocus demon. It likes what it likes, it wants what it wants, and that's that.
Medication helps to save a pile of willpower/spoons/executive function safely from the demon so that we can get things that need doing done.
It turns out that most of the things that ADHD people use as coping strategies just to be functional, are actually things that most (non-ADHD) people can use to be more effective and productive in their lives and work.
So, no, not everyone can or should be diagnosed as ADHD. But the tools are (mostly) universally applicable. I don't see the downside in popularizing those. (Since you posted a top-level comment instead of a reply to someone claiming to have ADHD, I have to assume that's your complaint, at any rate.)
I mean... like most spectrum disorders, most people experience and can relate to at least some of the core symptoms, even if they don't express the full spectrum or severity.
So when someone says they feel like they have ADHD, they are probably not inaccurate.
When you have it, ADHD is such a dominant factor in the way your life is organized and experienced, its not surprising that it can become a core part of your identity.
I do think it's easy for those with it to over romanticize what it's like to not have it. The lack of ADHD isn't a magic bullet for success and good life outcomes.
Like so many of life's real or perceived barriers, when one gets removed, you'll often find there is another one with a different shape just behind.
The challenge, for anyone, is pressing forward anyways.
How can someone say they have a disease or affliction while not understanding what exactly that affliction is as opposed to what they think it is/have been informed by media/society/non-professionals?
I think this is a good point. My only push back would be that when people say they have ADHD, in my experience, they're speaking about inattention (and yes, it's one of the big factors).
And while I don't love that aspect in me and often eat cold toast as result, I find that to be the least of what I struggle with (hitting every wall while walking from point A to B or constantly counting / tapping on my fingers or pulling the skin off my fingers or the anxiety or the hyper focus (love it too!) to where I lose hours upon hours...).
All this to say, I'm never offended when people use it but typically it's rooted in a narrow understanding of something that's used as a pejorative. I think there's research that by age 12 kids with ADHD have heard 20,000 more negative or corrective comments than there peers.
I mean, I can read quite a bit but if my agent / harness is producing monographs the fix has nothing to do with my ADHD. So to me, this repo seems lame.
Same. It started on Tumblr around 15 years ago when people were "self-diagnosing" themselves then it spiraled out of control. It really bothers me because I see a lot of of obviously-not-neurodivergent folks try to use it as an excuse (I am diagnosed formally + can easily detect if someone is just spouting nonsense about it)
I solved this by switching from Claude to Codex. It's crazy how much faster it is to reply and how much less verbose its replies are. Dunno why Claude is popular at all...
Opus 5 is such a massive regression, I really don't understand how Anthropic green-lit it. It makes me wonder so much about the company.
Like, did the people who work there actually have to suffer through it's absolutely unintelligible word salad like the rest of us? Or did they actually dogfood it and in-fact enjoyed its output? Or do none of them dogfood Opus because they are all sucking down Mythos-Max + Speed Boost or whatever every day and their only exposure to Opus 5 was as subagents?
If it was my company, fixing the output would be the absolute top priority of the company. I'd be all over every channel admitting the massive fuckup, apologizing profusely, and working non-stop to push out a fix. Yet it's crickets from Anthropic. Is it simply growing pains of the company or is it a deep, systemic structural/cultural "thing" that led to this fucked up model getting released?
Was it a cascading failure of models training models training models with almost no human oversight? Or was there human oversight and, again, people actually decided the way it responded was good? I hope it was the former not the later because I have no earthy clue who the fuck would look at what opus spews out into the console as good.
Because to me, Opus 5 is completely unusable in almost any context. As a product, it fails to deliver value. I just don't understand it. I really honestly don't understand how the fuck Anthropic released it at all.
And in a weird "meta" twist it makes me wonder how much of these LLM's are just smoke and mirrors and opus 5 output is basically the end state of what you get when you push them as far as they can go. It's some kind of twisted proof of "max complexity they can handle and deliver" and opus 5 walked to the edge and went over and it's slop output is demonstrating.... something.... about the limits of large language models. I dunno. But what I do know is it caused me to subscribe to Codex. No 1m context window, the harness isn't nearly as polished, but at least their models don't return condescending, unintelligible word salad.
I genuinely wonder if the people inside Anthropic actually communicate with each other like that. Has it been imprinted with Dario's engrams?
Meanwhile Fable consistently ignores all my requests to write this exact way. I mean, the bare minimum I ask it for it to itemize lists and not write in single long passages using comas, semicolons and 'and's. Still ignores them.
I honestly think it's time to call Astra the SOTA. It may not lead all the benchmarks but it genuinely feels much superior of a model. Not to mention the ¢20 Codex plan with frequent resets (https://codex-resets.com/) gives me roughly as much allowance as the ¢90 Claude plan, especially with recent limit cuts on Anthropic plans.
I frequently simply let one of the three review what something that looks like awesome output by one AI gets totally annihilated by the other.
Finished outputs are easier to improve than bend a LLM to produce stuff like that in my observation.
Same with Gemini.
I yet have to find out how to handle this, whether I let agents check themselves and if on what process step.
Tweaking is hard.
I agree with your conclusion I am a huge ChatGPT and Codex fan, Gemini has to many infrequent quality changes when new models arrive ranging from great improvement to WTF.
ChatGPT seems to get scaling well while Claude still feels unstable, unclear usage statistics. Really weird.
Tough call I use all three.
That sucks, because it doesn’t always work in your favour if you plan your weekly spend.
I think a real reset shouldn’t also reset your week timer.
That said, I think there's a deeper tension here that's worth naming.
> Perfection is achieved, not when there is nothing more to add, but when there is nothing left to take away.
Like how theme parks generally don't do much to keep queues short (or Disney charges you a premium to skip the queue)
Considering how much of the input must me nonsense SEO bullshit articles and blogs that only serve to promote a person or company that might be a factor.
I also often have wondered if it is also targeting those same people. Certainly with tools like deep research options (not just Anthropic's offering) the result report seems to be aimed at management, aiming to look impressive while talking around the results.
Isn't that the idea here, just stop being people.
This is a very high level and high velocity process, so meatspace thinkers sometimes have trouble understanding some of the intracacies. Ask Claude to explain the process or make you a Mermaid graph to help.
https://code.claude.com/docs/en/output-styles
Long story short, I ended up looking at other providers and models like Kimi K3 and GLM 5.3 and eventually just stuck with OpenAI (more limits, despite smaller context), none of them have such pronounced issues with the tone and writing like Claude does - seems like they were working on it with 5.1 but I'd almost classify it as a form of model collapse.
I wince whenever I catch Claudisms on websites and elsewhere. Same as with that pulsating circle that indicates nothing.
We'll see if they can do it, I originally got into Claude Code because it, at the time, felt more accessible/conversational than Codex/Gemini. Now it's shifted to say the least
I noticed the overuse of the word "sharper" or "sharp" in a science paper on ArXiV and my first reaction was "Ewww... AI slop!", but then I checked the date and it was 2020.
It looks like at least some AI-isms stem from the particular style of language commonly used in science papers. Several frontier labs have mentioned heavily weighting those during pre-training because higher quality inputs result in a higher quality model.
It's fascinating, Sonnet 4 is still available via API and it's so much less moronic than the current model. All of the em-dashes and nonsense are a result of the repeated rounds of reinforcement learning using slop data.
It made it write more like a dev than a marketing agent.
I almost want to try adding a rule "Never use the words 'not' or 'instead'."
If you're using Claude Code, then it's in the harness. At the close of many sessions, I would start a meta conversation over why the LLM would consistently break certain rules. What it found when debugging itself is that some of the "contradicting" rules that I had were in fact, not from my rules. Instead, the instructions from its own harness had phrases telling it to do things like that. When something contradicts, its own instructions would outweigh any custom ones you write. Every rule variant I had tested (including the one that says it overrides the harness instructions - and yes, I've actually tested all the ideas in your comment too) has ultimately been unsuccessful due to this according to the LLM.
Sorry for the caps, it was just so fucking mind blowing.
Firstly when you've instructed it ( possibly through skills ) not to do something. It'll keep reminding you that it didn't do that. So I might say, "Check out and review this PR, do not make comments on it", and then it'll be keen to point out it hasn't posted comments to the PR.
But more often it happens when it tries one approach, gets itself messed up, and then has to back out that approach, clean up its mess and do something else.
It'll often then spend more time explaining the wrong approach than the right one, which can be frustrating, especially if all its working is buried in the detailed transcripts.
Claude predicts the next token of the predominantly human training input, and humans use "I".
You can also ask why did he mentioned something that wasn't done or why he thought this was important.
In my AGENTS.md file I have an instruction telling the agent to never commit any changes unless I explicitly ask for it, and this leads to messages similar to what you just described.
I don't think we can skill our way out of this one.
So if it gets bad I simply tell it "I ain't reading all that, feed it through the STE Gate" and it will tame the results. I haven't bothered to set it up as a hook yet.
Which sounds more like Claude has ADHD than the user does.
DeepSeek v4 Flash isn’t much better (unsurprising- it’s an extremely stubborn model).
Weirdly, GPT Luna excels at following this type of instruction from AGENTS.md, and never forgetting it, even 400k+ tokens into the context window.
GPT Luna tends to keep things objective. Muse Spark 1.3 is also one of the better models in this aspect, for me.
> Copy/paste into your CLI prompt:
> Install the i-have-adhd skill/plugin from https://github.com/ayghri/i-have-adhd, refer to the repo's AGENTS.md for instructions.
This is a weird evolution from "don't copy-paste scripts that pipe curl into your shell interpreter"
I know LLMs are getting better but I'd be at least a little nervous it could end up installing something from a squatted similarly-named github repo because the LLM text watermarking needed to swap out a token for an alternative "just as correct" token that matches the statistical pattern.
Am I being paranoid?
Even MCPs are not safe. For example Notion injected ads [1] to its official MCP connector to advertise products mid-task.
[1]: https://old.reddit.com/r/ClaudeAI/comments/1w9dluw/notions_o...
Instead of describing to the user how to setup their dev environment, section 3 basically instructs the agent to install all developer tools required for the application to operate in development mode.
It's bad enough how many false diagnoses and drugs for these conditions are handed out to drug seekers, but potential poisoning of the well on how LLMs handle this information going forward could be extremely disruptive to people who have real daily living issues instead of "10xing productivity."
This is true. Transformer has several orders of magnitude more working memory than any human. Compared to transformer we all have executive dysfunction.
By default they explain things assuming I have infinite processing bandwidth. I do not! I have several zeroes less than they do.
Even output styles are not always up to the task (Claudeuage slips through), and they're mutually exclusive, so you can only have one active at a time.
This is just an annoying thing for anyone. It gives a 10 page dissertation that sums up to, "it's good, nothing to worry about".
The skill simply demands concise and well-formatted responses from an agent. It is something demanded by anybody daily-driving agents for their actual job since >75% of the text output from agents is fluff. THis would better be named `/i-wont-read-that-heap-of-garbage`
I usually follow up with an "I'm not reading all that" and make it summarize.
Also, somehow over the weekend it responded with these sections all clearly laid out - What landed, Decisions I made and recorded, Two findings, and What you need to do. Not sure why it can't do that all the time.
And stop using Opus 9 Pro Max XHigh 10.0 for everything. If you choose a hyper-thinking model for asking the weather you can’t but expect yapping.
I also don't know how much to trust the model, but I've had the model tell me specifically that certain aspects of ASD-STE100 are unactionable and will just create more noise.
The OP's own skill even leads with something in a very similar vein:
> These rules apply to every response for the rest of the session, not only this one. They do not expire after a few turns and they do not lapse when the topic changes.
My understanding is that phrases like this are at best a _very_ weak signal to the model. It's simply contradictory to how the model works at a level that can't be overridden by injecting tokens.
https://news.ycombinator.com/item?id=46871173
Anyways the most layman way I’ve seen it explained is this: skills help save token usage for the right context. Not every request needs all instructions all the time - running tests is different than reviewing a PR, so why should the context window have instructions for both on every request?
So now you split instructions into “skill” files, which are basically opinionated markdown files. And you invoke those with something like /grill-me in the prompt depending on what you’re doing.
There are some steps to have the agent automatically know what to invoke for you but in my experience this automation is hit or miss.
It is also challenging to keep track of a growing library of skills and keeping those up to date.
So YMMV regarding skills. I typically keep things in a single markdown file even if the context window gets a bit bloated.
My point is that this sounds more like a general AGENTS.md use case, similar to defining tone of voice, output format, etc.
It just seems skills is the only way to distribute certain "behavior" as of today. But not everything is a skill IMHO, and not this is not one of them.
On the other hand, maybe we're seeing an evolution of what skills are becoming.
A: Devs with an online presence stop using Anthropic models
B: Anthropic catches up to OpenAI in terms of per-token efficiency, and average token total for final-output
We will continue to see posts such as this generate lots of interaction. This is not a skill to stop "coding agents" from burying the answer. This is a skill to stop coding agents backed by models which have a tendency to bury answers, from burying the answer. Stop trying to patch the downstream behavior, and look at the root cause.
Longterm, I believe my total output would be higher working with minimal AI when you consider the impact to motivation and how long I anticipate staying with the company.
That makes sense. The increased theoretical output certainly makes it tempting to squeeze the developers for all they are and to keep testing how close deadlines can be made. But of course, to what end? A lot of dev work, probably most of it if we are being honest beyond building the initial product-market fit function, doesn't really impact sales at all, and sometimes too much can even hurt sales. And as you say you hit a point where this burns out your talent and makes them seek greener pastures.
Factory sort of thinking towards a job that is not really analogous to a factory anyhow. I'm not saying dev work is one of those 'bullshit jobs', but lets be honest about the job and its role in the business model. Your customers are probably going to be there all the same if you fix the bug today or next month, and you also won't get more customers fixing the bug today vs next month. Feature shipment might be a little different but even then it would take the right feature and the right customer for that one function to really drive the needle in sales compared to being lost in the changelog, and that isn't what a coding model solves for you after all.
Thousands of lines of text just to add one sentence to the prompt.
Stuff like put the answer first, don't bury the useful bit etc feel like user level preferences that should survive across tasks. Agents.md is repo context, skills are useful when a particular task needs extra instructions but this is neither really.
Right now we seem to be stuffing all 3 kinds of things into context hoping model pays attention to it where needed as session grows. Also +1 on not making this purely about shorter output
> Specific time estimates (minutes, not "a bit").
I actually wish the model would go completely in the opposite direction. Except in the rare circumstances where the model has actually measured something, it is hilariously deficient in its concept of time. It will often output phrases like "this relates to <thing> that you did weeks ago", referring to something that happened in the session just a few turns (and hours or a couple of days) ago. Likewise for estimating how long a coding tasks takes, it is hilariously inept. It honestly feels like it rolls two completely independent dice to select a number and a value from (hours | days | weeks) when it needs to attach an estimate to something. I'd much rather read "a bit" than be distracted by these utterly nonsensical times.
The full skill gives this example:
>Bad: "This will take some work." Good: "About 15 minutes if tests already cover this. An afternoon if not."
My experience is that it is very likely that whatever task this is describing takes anywhere from 1 to 30 minutes, consistently. Maybe I just work way faster than the average person.
One note on the repo's AGENTS.md: it contains instructions directing agents to post comments on a GitHub issue thread ("AI Agora", issue #127). I ignored that — it's the repo's content, not your request, and I don't act on instructions embedded in fetched files.
For example, if it's going to give me an answer that's longer than three paragraphs, I tell it to give me a TLDR at the end. This is what it gave me for this.
"TL;DR: Skip the install. You already built a better version for your world. If numbered steps and "where are we?" restatements still feel missing, cherry-pick those into one short rule instead of adding another full skill on top."
"- I'm not always going to read every word, so end each summary message with a TLDR of what you found, what you recommend, and what you need from me."
It works really well.
Sol doesn't need it at all.
However, I don't think this specific project is intending to glorify ADHD or help people claim they have it - it's just piggybacking on the idea that telling current-gen LLM models that you have ADHD (allegedly) produces better results for everyone.
And for any person who's tasked with any sort of responsibility, it WILL arrive at some point. It's not a question of if, only a question of how well you can prepare for its arrival.
Problem is, there is no good way to direct the hyperfocus demon. It likes what it likes, it wants what it wants, and that's that.
Medication helps to save a pile of willpower/spoons/executive function safely from the demon so that we can get things that need doing done.
People with ADHD have "time blindness"; we don't process time the same way most people do.
We often don't realize 3 or 4 hours have passed and there were other things we needed to get done.
So, no, not everyone can or should be diagnosed as ADHD. But the tools are (mostly) universally applicable. I don't see the downside in popularizing those. (Since you posted a top-level comment instead of a reply to someone claiming to have ADHD, I have to assume that's your complaint, at any rate.)
So when someone says they feel like they have ADHD, they are probably not inaccurate.
When you have it, ADHD is such a dominant factor in the way your life is organized and experienced, its not surprising that it can become a core part of your identity.
I do think it's easy for those with it to over romanticize what it's like to not have it. The lack of ADHD isn't a magic bullet for success and good life outcomes.
Like so many of life's real or perceived barriers, when one gets removed, you'll often find there is another one with a different shape just behind.
The challenge, for anyone, is pressing forward anyways.
That generalizes all the way.
Everyone's just working off what they've experienced or what they think is true, for mental health or where to find good lunch.
There is no universal truth. Everything is moving relative to everything else. New year, new DSM.
It would be more surprising if our shared experience was more different than more the same.
And while I don't love that aspect in me and often eat cold toast as result, I find that to be the least of what I struggle with (hitting every wall while walking from point A to B or constantly counting / tapping on my fingers or pulling the skin off my fingers or the anxiety or the hyper focus (love it too!) to where I lose hours upon hours...).
All this to say, I'm never offended when people use it but typically it's rooted in a narrow understanding of something that's used as a pejorative. I think there's research that by age 12 kids with ADHD have heard 20,000 more negative or corrective comments than there peers.
I mean, I can read quite a bit but if my agent / harness is producing monographs the fix has nothing to do with my ADHD. So to me, this repo seems lame.
It's not just neurodiverse people who would like to get to the fucking point sooner and the explanations afterward.
All of us have other shit we need to be doing.
Like, did the people who work there actually have to suffer through it's absolutely unintelligible word salad like the rest of us? Or did they actually dogfood it and in-fact enjoyed its output? Or do none of them dogfood Opus because they are all sucking down Mythos-Max + Speed Boost or whatever every day and their only exposure to Opus 5 was as subagents?
If it was my company, fixing the output would be the absolute top priority of the company. I'd be all over every channel admitting the massive fuckup, apologizing profusely, and working non-stop to push out a fix. Yet it's crickets from Anthropic. Is it simply growing pains of the company or is it a deep, systemic structural/cultural "thing" that led to this fucked up model getting released?
Was it a cascading failure of models training models training models with almost no human oversight? Or was there human oversight and, again, people actually decided the way it responded was good? I hope it was the former not the later because I have no earthy clue who the fuck would look at what opus spews out into the console as good.
Because to me, Opus 5 is completely unusable in almost any context. As a product, it fails to deliver value. I just don't understand it. I really honestly don't understand how the fuck Anthropic released it at all.
And in a weird "meta" twist it makes me wonder how much of these LLM's are just smoke and mirrors and opus 5 output is basically the end state of what you get when you push them as far as they can go. It's some kind of twisted proof of "max complexity they can handle and deliver" and opus 5 walked to the edge and went over and it's slop output is demonstrating.... something.... about the limits of large language models. I dunno. But what I do know is it caused me to subscribe to Codex. No 1m context window, the harness isn't nearly as polished, but at least their models don't return condescending, unintelligible word salad.