No, how is that better?

The example is unambiguous. Your modification is ambiguous at best. <failure to ensure aws credentials are correct> != <aws credentials are incorrect>

The actual STE standard would score horrendously in a college essay. STE encourages simplification and tons of repetition of words that is discouraged by college professors. It is designed to be clear technical writing for people with a loose grasp of English. College writing encourages complex sentence structure, varied word choice for the same concept and other things that make the writing more interesting at the expense of clarity.

Violates rule 4.2: Do not omit words or use contractions to shorten sentences. Keep articles, keep "that".

nice :-) i'll try that! thx

Honestly I should use this on my own emails and slack messages.

Ccn't say, though since Opus 5 I'm much more often staring at the wall of text and I have no idea what it's telling me.

WTFs per prompt metric raised sharply for me :)

Based on what? I wouldn’t have learned about ASD-STE100 if I hadn’t stumbled upon this post. I’m not even going to use the linked GitHub project, just mentioning ASD-STE100 spec in certain prompts makes them useful.

Since your claim that adhering to a proven style guide is useless slop is not itself useless slop, I am looking forward to your empirical evidence or formal proof that there is no benefit to using it.

Maybe your complaining wasn’t worth a comment on Hackernews?

You didn’t link to it but I looked back at my very few submissions and realized that I had posted it in 2019. I thought it sounded familiar!

Potentially related to https://news.ycombinator.com/item?id=49068179

Both. Command the author to use the style, then command a reviewer to check it. Write one skill called review-prose with your rules, and another called write prose which tells the author they will be judged by review-prose, so you only write the rules once.

What I have found is that getting a model to rewrite a badly written passage is hard, because it seems to key off what it reads. It might swap some vocabulary around ok, but it doesn't fix structures very well. So getting it close to the preferred style in the first place is better.

To take this further, if you must fix existing bad prose, write a clean-prose skill which extracts the bare structure of the prose with none of the style, hands it to an author subagent who isn't poisoned with the original bad prose, then hands the output to a reviewer subagent.

Opus 5 writing is horrendous, so I have been experimenting with improving the output!

Here is the revised post title that follows ASD‑STE100 Simplified Technical English rules:

"Agent Skill to Enforce ASD-STE100 Simplified Technical English in Documents"

What a wonderful skill. I hate the long and verbose do strings or docs LLMs spit out. This will make a great addition to my docu agent.

And I agree, maybe I should use this for my emails too

The readme looks to me concise and correct. Tested it and it works. Better than many human-written readmes I've seen around.

The problem with at least ChatGPT is no matter what personality you set it still reads like a smug asshole trying to sound smart.

Some of this may be perception rather than reality. I have never felt that ChatGPT was being smug or rude to me.

And the goddamn emojis. I get it, people use them when texting to make the writing a bit more chummy, but I can really live without them everywhere else.

I've been using a plain ASD-STE100 prompt for a little bit now, and while I somewhat prefer the text that agents produce while being told to use simplified English, it does not necessarily change the overall structure of what they write. It just now tends to have shorter sentences, and fewer drumroll, pitch-deck / vacuous section titles like "the finding that pivots the preposition", etc. Overall a significant quality increase in my opinion, but nothing earth shattering, and doesn't fully solve the problem.

I wish this were selectable as the default output style.

Just to clarify: a skill isn't the same as a plugin.

I've added the prompt to use the ASD English, on my CLAUDE.md when I learnt of the standard. The generated output is more tolerable to read, and is less confusing.

I like it, and I'll also try the Economist one on another thread here. I have global instructions on how Claude should try to write things like I do.

I generally avoid having lots of skills, security risk as I won't vet them all.

The pretraining data isn't getting muddled, the instruction just gets in the lossy middle, and there's less for attention to grab on to. If you repeated the prompt with a hook every turn, it'd stay quite sharp.

The training material is used to "develop intelligence" not as reference material.

As an analogy, students learn a bunch of things during school, become more intelligent, but do not retain explicit knowledge like all of the details on the periodic table, or all of the exact formulas for things.

No semicolons — write two sentences.

Oh lord.

The day I have to negotiate and persuade the machine to stop talking shit rather than command it is the day I decide fuck it and go and farm geese or something.

Smells like today. I’ll take goose shit over this.

Precommit hook

I use it with a rule package that has a variety of Vale styles for AI writing tells (github.com/tbhb/vale-ai-tells). Typically I have it set up in a project and then gate the agent with post tool use hooks and pre-commit hooks. It's far from perfect but it does help eliminate a lot of the common tells.

STE is part of the training set, so the skill is redundant and only pollutes your context window.

The very first sections of the README having obvious claude-isms is not very reassuring:

AI slop dies as a side effect

One folder, no dependencies, MIT.

Also from a nicely explained YouTube video: https://www.youtube.com/watch?v=uJblcC4lKYw " The cure for AI slop is a 1986 aircraft manual"

https://github.com/woosal1337/blog/tree/main/videos/ep01-the...

https://www.npmjs.com/package/is-odd

Also skills can often include helper scripts or other binaries which the agent can use to do things it couldn't otherwise.

It can easily detect repeated failed attempts at a non obvious problem such as incorrect documentation or missing run flags

Technically speaking: it can't, any more than it can actually answer any other thing you ask it to do.

But in practice it does produce fairly reasonable output fairly often, and if you've been there watching and correcting it you can probably validate the result quite easily. "Re-read everything before" and similar are definitely anthropomorphizing, but that doesn't mean they're ineffective.

Why wouldn’t it?

One observation: ask an LLM to write a skill, it tends to make them overly verbose and prescriptive. Often, something briefer and human-written actually works better

Incredibly so. All too often a “hey, you shouldn’t have done that here” turns into “NEVER X”, without it actually understanding or making an effort to understand why the correction was made, though I would say usually the context to do so should suffice. I have a rule for it to reason this through and use nuanced language and would say the frontier GPTs (5.4 to 5.6 Sol) get it right around half of the time (very rough estimate). The conclusions are really dumb sometimes.

I’d be interested in an expertly crafted skill here, maybe there are things about it you can still improve. This is an area in which I still find LLMs to be quite lacking.

It also made me appreciate the complexity of the nuances and levels of indirection of what I want to teach it: “Upload to the remote host, which in this case is this but might be another one in another use case, only do this on the local system and this on the remote, do this to X unless Y …, prefer doing Z unless another rule overrides it …”

I sometimes feel like there could be a more expressive way to structure to structure these rules (bring the snark!).

Yep. That is what I do too. But a lot of times the changes it makes are bandaids rather than addressing root cause. I have to periodically evaluate the skills for consistency and opportunities for simplification.

Super valuable and actionable advice. :100:

Oh, skills are absolutely useful for giving the LLM distilled knowledge of things that it doesn't just know ("off the top of its head" so to speak). For example, a company's coding style guide is something that could be very useful to express as a skill.

Not true. At work I have skills for different sets of APIs for different scenarios. That saves some prompt bloat because you rarely need to straddle projects. So you just load whatever you're using and don't have to maintain a a giant prompt.

My agent skills are just sets of instructions for my preferred way for something to be done. Mostly code reviews listing classes of bugs and output format and the like.

But also development instructions focusing on how and what to research before implementing (some of the stuff I do ends up heavily influenced by papers and publications while the naïve implementation is often bad, old, or gets stuck.

Projects like SkillOpt[1] are pretty good evidence that the ceiling for skills isn't "describe it in a sentence and let the LLM generate it". There's value in iterating on a skill and figuring out what the weak parts are. At that point, sharing the skill can indeed be useful. Just look at superpowers, GSD, etc. They're 'just' skills (and a few bash scripts), but the text in them is useful enough to share.

[1] https://microsoft.github.io/SkillOpt/docs/guideline.html

Yes the prompt "only output ASD-STE100 Simplified Technical English" does the same thing as the skill.

But it's very useful and skills is a good way to share promots, so whatever.

Try the skill or the prompt. It will likely improve your experience interacting with agents

I have something like "no over enthusiasm, and less marketing please. Also I have ADHD and therefore get distracted easily" in my agents.md. It made responses way more digestible and to the point.

Man, I was just now imploring Claude to be more concise.

Flight fire with fire!

LLMs should be unreasonably good at exactly this kind of writing because they’re good translators; regardless in practice it works well to deslopify their writing, been using this in all my prompting in the last week or so, haven’t seen a single load bearing belt and suspenders since.

Love this line in the critical material quoted there:

“Writing correctly in STE is not an easy task as it requires a good command of the English language together with a good knowledge of the matter of the writing.”

This is simply what is required for good writing (in English) in any domain with or without STE.

The point of STE is to support technical writers who have knowledge of the matter and a style guide. In other words, STE will not make something unambiguous simply by replacing words. The example sentence is just to illustrate a grammar rule: "test" as a verb vs a noun. That is all. You should not assume an STE rule will disambiguate a single sentence pulled out of context.

I don't know if I have been damaged by reading so much AI, but I swear the narrator of that video had the script for it written by Claude without any of those rules applied. There are so many platitudes and AI-isms in the way he speaks:

    "now the honesty - those translation gains were real but small"
    "and here is the honest part"
    "same disease but with different symptom"
    "so that brutal 3% number was a Claude quirk, not a law of nature"

Use gpt ⁵. ⁵or⁶

Clause is a token torment machine that licks your balls while stealing your wallet

yes it does - https://github.com/hsaliak/std_slop/blob/main/system_prompt....

I've added the same thing to the system prompt of the internal agent I wrote for work, which talks to claude models. I have not gone into the details on whether it adheres to the format exactly, but i do see visibly less slop and less marketing nonsense in the Assistant messages.

Didnt use it on the readme for the repo

TIL There's a spec for how I normally communicate instructions at work.

the problem I’ve found with these things is that models drift immediately. if it’s not a git commit hook that runs over docs and comments and commit messages objectively it’s probably useless. which I might try.

Claude is so friggin wordy and has no idea how place comments iff they actually matter.

You can't de-slop it you can only make it less slop.

AI slop doesn't die at all.

The “tired mechanic” is apocryphal at best. ASD was intended to be clear to non-native speakers. Here’s an example from another page:

THE SYNTHETIC LUBRICATING OIL USED IN THIS ENGINE CONTAINS ADDITIVES WHICH, IF ALLOWED TO COME INTO CONTACT WITH THE SKIN FOR PROLONGED PERIODS, CAN BE TOXIC THROUGH ABSORPTION.

In STE this sentence appears as below:

DO NOT GET THE ENGINE OIL ON YOUR SKIN. THE OIL IS POISONOUS. IT CAN GO THROUGH YOUR SKIN AND INTO YOUR BODY.

Consider if you translated those phrases into a foreign language you’re basically familiar with. You can be awake as you want and mis-interpret the first one.

https://nitter.net/geogristle/status/2078492579511906771

Cruft complaints aside, what are people actually doing about this? Claude's prose output is becoming incomprehensible as its coding skill increases, and the concepts it needs to express are becoming more complex as it can handle more complex tasks.

I don't understand the challenges involved super well but I feel like this might be better as a piece of actual code (like a linter) that you can run to have an LLM iteratively de-slop its own writing, rather than forcing it out of distribution and having to contend with all the unreliability that entails.

I tried "be concise and respond in a blunt tone" and all that did was add a section to the bottom of every response "here's the blunt concise truth <1 million bullet points>"

It definitely seems like this should be a post processing layer instead of an instruction.

You don't need any of this slop. Just add this to your AGENTS.md file, jesus christ.

"When writing plans or documentation use:

ASD-STE100 Simplified Technical English (STE for short)"

I didn't know this even existed. Thanks for sharing.

I have a question about how did the project evaluate the technical English performance compared to other skills/MCPs and with LLM w/o skills? In the Github repo, there is a summary of "measured: 6 Claude models × 8 tasks × 2 conditions, 96 runs", Does it means the percentage of violations in the words? If that's the case, the measurement might be a little bit strange weather the STE measure is already in the prompt? STE violations per 100 words ▼ 72.9% (every model won). The bench or evaluation should not be in the same prompt, like eval/test.

The examples are not good. In one example (incident report) the agent turns a generic "something went wrong" into overly precise error descriptions that may or may not spill internal details. Then it proceeds to make a promise to implement a persistent monitoring for that problem this week.

I mean generally this wouldn't be considered a bad response, but it is deeply problematic if an LLM tasked to just simplify language added both internals and promises to your customers without your knowledge.

AH. https://github.com/computer-reinvention/trie

Sorry. A missing hyphen!

I wonder whether the real value is the shared, versioned workflow rather than the prompt itself.

Uh, nice! I hadn't heard about that spec before. I'll give the skill a try.

I often ask it to aim for a Flesch-Kincaid Readibility Ease Score of around 50, with good results. ELI5 is good too where appropriate.

I'll add ASD-STE100 to my list of decorposlopification strategies.

I like this. Agent-facing docs feel more like an interface than prose

printingpress.dev project is crying out for this skill.

Anecdote: was testing Opus 5 and even ASD-STE100 cannot save you from its meta-commentary and signposting all the time. It writes what it wants to write, e.g. "here's where you are right/wrong" instead of "Your instinct of the shape is right, but here's a sharper version". I could not get it to stop doing that.

In contrast if you ask GPT 5.5/5.6 to speak directly/plainly, it will just straight up tell you the content "X is right, Y is wrong". Much preferable.

I've been using this method for about a week - great outcomes from it so far: clear, clean language that sounds like something someone would actually write.

tried it out - wrote really basic and then also ai slop - i love the idea of creating context collisions but this particular skill needs an inverse reference that takes the model through the latent space to remove the ai slop - its got legs but I'd consider mixing it with some advertising principles or storytelling so it trains out the mic drop bs