10 ms·

Agent Skills

bsoles 4mo ago
Agent skills are ways of turning over our means of (software) production to our employers, while making ourselves obsolete at the same time. In the recent past, a (software) professional had to be continuously employed by their employer to maintain access to their professional skills. By transferring our skills into AI agent skills, we are basically giving away that privilege. In the near future, our employers might feel they don't need our skills anymore because it has already been captured by the AI agents. Somebody with a better grasp of economic history should be able to explain this using the analogy of what happened during industrial revolution and how the workers got screwed over.
cavisne 4mo ago
The problem with all these skill frameworks is when you are deep enough into AI coding to write one - your brain just cannot handle actually putting effort into it. These are all written by AI, and the authors skim read them. It’s better to do the maybe 2 hours of human effort the authors put into them yourself for your own workflow.
dhr_uvi 4mo ago
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saluc28 5mo ago
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encoderer 5mo ago
I adopted a couple of these, the api design and ui testing ones have been particularly helpful.
y-curious 5mo ago
Thanks for this, going to steal a lot of this. I would install your plugin, but I worry about being able to delete it later. I also think that each one of these is better served customized to a developer. That said, I'm still going to grab some of these, thanks!
- bvirkler 5mo ago
  A plugin is just a set of files, right? why wouldn't you be able to delete it later?
ElijahLynn 5mo ago
I've been using Agent Skills on a new side project and I'm really impressed so far! It really holds my hand a lot of the way and really lets me focus on developing a product instead of figuring out how to build it. I get to focus much more energy on high level architecture and product design. Very grateful for this repository and everyone who contributed to it!
CharlesW 5mo ago
From an SEO/LLMO perspective, the discoverability of these skills will be difficult without a rename: https://agentskills.io/ https://agentskills.io/ If Addy reads this, how do you pitch this vs. Superpowers? https://github.com/obra/superpowers https://github.com/obra/superpowers
- consumer451 5mo ago
  I would love to know how many people are actually using superpowers. I showed up on the agentic dev scene prior to superpowers, and I am getting concerned that >50% of my self-rolled processes are now covered by superpowers. I no longer trust gh stars, can anyone chime in? Is superpowers now truly adopted? If it is truly valuable, why hasn't Boris integrated the concepts yet?
  - nullstyle 5mo ago
    I just removed superpowers from my own setup. In my opinion, given the quality of the planning modes in both claude code and codex, superpowers was really just slowing things down and burning more tokens than vanilla.
    - consumer451 5mo ago
      Thank you for the data point. To give back as much as I can, I use the two built-in CC review processes when appropriate. But, those only do "is this PR good code?" Far too late did I finally roll my own custom review skill that tests: "does this PR accomplish what the specs required?" If I could ask for one more vanilla CC skill, it might be that. However, maybe rolling your own repo-aware skill via prompt is better?
    - horsawlarway 5mo ago
      anecdata, but I ended up in the same spot. I used superpowers - but it burns waay more tokens for basically the same outcome as a single line that states "Please do planning and ask any required questions before implementing. [my prompt]" On the latest models and with a decent harness, the planning modes are quite good, and the single sentence telling it to ask you questions lets the model pick the right thing to ask about, instead of wasting a bunch of time/tokens on predefined skills that try to force basically the same result. It does introduce a second set of required interactions, but you can have another agent be your "questions answerer" if you need it (result quality goes down a bit vs answering myself, but still quite good, especially if you spend a bit of time on the answerer prompt) Basically - things are moving fast enough I'm not convinced buying into superpowers/agentskills/[daily prompt magic beans]/etc tooling really makes sense. I'd stick to the defaults in the harness for most cases, and then work on being clear with the ask.
stevenpetryk 5mo ago
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gosukiwi 5mo ago
I wonder how does this compare to superpowers
senko 5mo ago
> This isn’t a coincidence. It’s the same SDLC every functioning engineering organisation runs, just in different vocabulary. [...] Amazon calls it the working-backwards memo and the bar raiser. Every healthy team has some version of this loop. This (sdlc == working backwards & bar raiser) is so horribly wrong, that I hope this was an LLM hallucination. In general, I'm starting to see these agent scaffolding systems as an anti-pattern: people obsess over systems for guiding agents and construct elaborate rube-goldberg machines and then others cargo-cult them wholesale, in an effort to optimize and control a random process and minimize human involvement.
- BOOSTERHIDROGEN 5mo ago
  This is how similarly we collectively approach Taylorism, isn't it? However, the world favors capitalism, of which Taylorism becomes a handy scaffolding.
- yks 5mo ago
  The problem is it’s so rarely A/B tested, definitely not at scale. An engineer, who writes all these my-workflow-but-for-agents skills, proceeds to get the good outcome, while also seeing affirmations that the agent did follow the prescribed processes - that is considered a victory. In reality the outcome could’ve been just as good if they fed Claude a spec + acceptance criteria, or even a basic prompt for the simpler tasks.
  - AndyNemmity 5mo ago
    Yeah, I Blind A/B test everything, and a lot. But I don't expect anyone to every use my stuff. It's complicated as hell. But it's for me, and it works without me having to remotely think about the complexity. I love that.
- PleasureBot 5mo ago
  All of these articles about setting up the perfect agent environments with skills, plugins, MCP servers, markdown files, etc. etc. reminds me so much of the culture around setting up the perfect "productivity stack". You need the perfect note-tacking app, ticketing app, calendar integrations, yada yada before you can really do anything meaningful. The reality is that you're going to get beat by someone with a few things written down on a piece of paper who is just getting stuff done.
gavmor 5mo ago
Naming things is such a hard problem that many devs don't even bother trying. That being said, this post is full of reasonable assertions, so I'm looking forward to experimenting with this... whatever it is.
- fragmede 5mo ago
  Wait, shit, are people using LLMs to name things now? I'm definitely out of a job then!
  - kigiri 5mo ago
    Naming things is my principal use for AI, I don't always pick a name from the suggested ones but it sure help me find better ones.
  - gavmor 4mo ago
    I'm notorious for taking poetic license with naming—that's how we end up with `class Escutcheon`, or variables `recto` and `verso` where applicable in eg PDF generation. But as much pleasure as I derive from novelty and specificity, my colleagues have oft expressed perplexity—whereas the terms which LLMs produce hew closer to the manifold (by definition!) and raise fewer eyebrows. So, it has its turn.
turlockmike 5mo ago
The best way to prompt an LLM is to describe the outcome you want, that's it. They are trained as task completers. A clear outcome is way better than a process. If the LLM fails, either you didn't describe your outcome sufficiently or is misinterpreted what you said or it couldn't do it (rare). Common errors should be encoded as context for future similar tasks, don't bloat skills with stuff that isn't shown to be necessary.
- alexjurkiewicz 5mo ago
  I agree that many skills are overblown and unnecessary. But there's a lot of value in giving AI the right process. See how much more effective Claude can be for moderate or large changes when using the superpowers skill.
- peab 5mo ago
  a skill is just reusuable/shareable context. It's just text, really. It's useful for things like documentation on how to use an API (this works better than MCP in my opinion), or a non consensus way of doing something. For example, you can use remotion to generate video. There are useful remotion skills that allow you to reliably generate specific types of videos. Captions of a certain style, for example.
- tecoholic 5mo ago
  If there is anything we have learned in decades of Software engineering, it's "A clear outcome" is not easy to describe. In many cases, it's impossible unless people from 4 different domains collaborate. That's why process matters. It allows for software to be built is a "semi-standardized" way that can allow iterations to get us closed towards the expected outcome, that might emerge over time. Yes, not everything I use LLMs for going to have the same level of ambiguity or complex requirements. Optimizing by choosing to skip over parts of the process is exactly Addy is talking in this article.
- stingraycharles 5mo ago
  > The best way to prompt an LLM is to describe the outcome you want, that's it. They are trained as task completers. A clear outcome is way better than a process. This is not true for anything complex. They’re instruction followers, of which task completion is just one facet. They’re also extremely eager to complete tasks without enough information, and do it wrongly. In the case of just describing task completion, despite your best efforts, there are always some oversights or things you didn’t even realize were underspecified. So it helps a lot to add some process around it, eg “look up relevant project conventions and information. think through how to complete the task. ask me clarifying questions to resolve ambiguities. blah blah”. This type of prompt will also help with the new Opus 4.7 adaptive thinking to ensure it thinks through the task properly.
zmmmmm 5mo ago
I was surprised how long some of these skills are. They are pages and pages long with tables and checkbox lists and code examples, etc. Curious how normal that is - it would only take a couple of these to really fill the context alot.
- tecoholic 5mo ago
  I have written zero skills, so not sure how normal it is. I counted the words in couple of them and they seem to be around 2k range. So 5 skills would be around 10K. Even at a small LLM context of 128k, that's still around 10%. And for a 1M context window like the big ones, it barely registers.
- sergiotapia 5mo ago
  I reviewed the line counts of my own project skill files, and the top 3 I have are: 805 lines 660 lines 511 lines Maybe I am _too_ conservative here. Lots to explore.
  - mohamedkoubaa 5mo ago
    No, you aren't.
- gwerbin 5mo ago
  I quickly skimmed and it looks like at least a few of them are intended to be more like system prompts for a tightly scoped sub agent than a skill as such. I agree, I wouldn't want to use a lot of of these in a longer-running work session. I have been successful with short and focused skills so far. I treat them as a reusable snippet of context, but small ones. For example a couple of paragraphs at most about how to use Python in my project and how to run unit tests. I also have several short "info" skills that don't actually provide the agent instructions, they merely contain useful contextual information that the agent can choose to pull in if needed. Even having too many skills can be an issue because the list of skill names and their descriptions all end up in the context at some point.
- umeshunni 5mo ago
  > it would only take a couple of these to really fill the context alot. Only skill front-matter (name, description, triggers etc) are loaded within context by default, so this isn't likely to happen without 1000s of skills.
AndyNemmity 5mo ago
This is why I created the /do router, to route to all skills. I also have anti rationalization, progressive context discovery etc. I only make it for me, so it's a bit complex and targeted towards me, and what I do, but it's pretty easy to adjust things. https://github.com/notque/vexjoy-agent https://github.com/notque/vexjoy-agent Working on reading through Agent Skills, it seems we've converged on a lot of the same points, and I've never seen it, so trying to get an understanding of it. Edit 1: I don't like all the commands. I just rely on a single router to automatically decide what I want, and that feels like the most reasonable way to me to communicate with it. I don't want to remember things. And that's the way for me to scale the number of skills and activities. I don't have to think about them. Edit 2: We have very different routers. https://github.com/addyosmani/agent-skills/blob/f504276d8e074912f4763e6163b436a4ffc74d0d/skills/using-agent-skills/SKILL.md?plain=1#L2 https://github.com/addyosmani/agent-skills/blob/f504276d8e07... vs https://github.com/notque/vexjoy-agent/blob/main/skills/do/SKILL.md https://github.com/notque/vexjoy-agent/blob/main/skills/do/S... I personally wouldn't call theirs an intelligent router. They are dancing between a few different skills. We have extremely different setups there. But of course, I'm using way more context to get it done. I'm even sending it out to Haiku to build the route choices. I choose to use tokens to make things better for myself, not everyone would make the same choice, so I certainly see why they are using a few skills, and composing them. Edit 3: This is much easier for a user to wrap their head around because there's much less. I am only focused on the best improvements I can make that show value for my use cases. This is straight foward to reason about. This seems like a nice way to get the best concepts for people trying to understand them. I commend them for a clean, simple approach. Edit 4: Yeah, I think there are some things I can learn from them which is always good. I especially like simple decisions like collapsing the install details for each harness in the readme. I'm going to read over the entire thing and look for opportunities to improve my stuff. We are all working together, learning, testing, building, trying to find the best way to implement things.
codemog 5mo ago
Everyone who writes this kind of stuff skips the boring parts: science and engineering. Yep, benchmarks, comparisons of with/without, samples of generated code with/without. This kind of stuff matters, and you may be making your agent stupider or getting worse results without real analysis. Also this prose reads like the author has drunk the Google kool-aid and not much else.
ai_fry_ur_brain 5mo ago
Cant wait for everyone to realize they've wasted a year + messing with agents and experiencing a feeling of psuedo productivity.
- wahnfrieden 5mo ago
  You haven’t made money from their use yet?
- pantheragmb 5mo ago
  I couldn't agree more, just because I know I already wasted months and pulled the plug :D
- nothinkjustai 5mo ago
  You’ll get downvoted for this hearsay!
  - footy 5mo ago
    I think you mean heresy. But maybe I don't get the reference you're making when you say hearsay
    - IncRnd 5mo ago
      Hearsay is a rumor or something that can't be verified.
      - footy 5mo ago
        I'm aware.
    - bot403 5mo ago
      I'm wondering if there are anti-ai bots trolling the boards. Look at all the usernames of the negative AI posts. Or maybe the only people left opposing AI are so hardcore against it they form their identity (username) around it
cpharsh410 5mo ago
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dmix 5mo ago
I've tried these larger agent skillsets in the past and felt it was a waste of time because it was just doing too much. Just like vim it's often better to pick and choose from the community instead of installing skills like they are an IDE. Skills are way too personal because every dev and dev team is different. So better to treat these as a reference for your own config rather than bulk install someone else's config.
- sunaookami 5mo ago
  Same for MCPs and system instructions, there are a lot of people that just install everything without understanding it, cluttering their context, wasting >50k tokens for these tools they don't need and then complain that they need to pay >100$ per month because they reach their limits too fast.
Amber-chen 5mo ago
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thatmf 5mo ago
Why are people so excited to put themselves out of a job? Not that these or any "skills" will do that, but just- in principle. This is like alienation from labor at scale.
- clapthewind 5mo ago
  Some people are playing the global optimization game; a world where anyone can have any (production grade) software they want.
- hibikir 5mo ago
  Because we've been automating large parts of our former jobs for decades. Otherwise we'd all be trying to build things in the least efficient way possible to maximize how long the job takes, which IMO isn't a great idea. Humans have been minimizing how much work is needed to get a certain level of output for as long as we can track. It's civilization. Should we go back to farming by hand with hoes, to maximize labor used? Go back to streetlights that are individually lit? The society that falls behind on automation becomes poorer, and eventually just dies, as even the people born there tend to choose to leave to higher productivity places. It happened to eastern europe, it happens to the Amish. To any poor society which gets emigration. Doing more with less has always been exciting.
- dewey 5mo ago
  Because usually the people who lose their jobs are people who do not adapt to the market. Right now it's not clear in which direction everything is involving and that's why people experiment with handing all their data to random agents, figuring out how to store and access context, re-use prompts and other attempts to harness this tech. Most of these will maybe be useless in a year as they might be deeply integrated into the next wave of models but staying on top of the development has always been part of the fun of working in this field.
  - kiba 5mo ago
    People are building bots to do the most legible thing possible which is feature in X amount of time. But it doesn't matter if the bottleneck is human thinking time required to output quality code rather than X amount of code written.
konaraddi 5mo ago
There’s so many ways, many redundant, to set up agents for software development that beyond personal/team/org needs+tastes, I need to look into setting up some benchmarks to evaluate what set up is optimal or whether the differences are even worth it.
SudheerTammini 5mo ago
Recently I have got an access(enterprise)to the latest ChatGPT module with an ability to write skills to automate repeatable taks. Without any prior knowledge I just started tinkering and now after creating and testing multiple skills in real business environment I can confidently say writing a good skill is a skill itself. As the author mentioned it's not an essay but a specific instructions sets organised in steps and in a concise manner.
theahura 5mo ago
I really wish he wouldn't use AI to write his posts. It would be faster to just post the prompt he used to write the article
- petesergeant 5mo ago
  I wish this fucking meme of "post the prompt" would die. Very little work is one-shotted, very little has a singular "the prompt", most is iterated until it's close to the vision of what the author actually set out to write.
  - rossant 5mo ago
    Exactly. Glad to see someone else articulate this so clearly.
panavm 5mo ago
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wg0 5mo ago
Snake oil. Good to read for sure. Seems all plausible too. But snake oil nevertheless. Here's why: The slot machine can drop any hard requirement that you specifically in your AGENTS.md, memory.md or your dozens of skill markdowns. Pretty much guaranteed. These harnesses approaches pretend as if LLMs are strict and perfect rule followers and the only problem is not being able to specify enough rules clearly enough. That's fundamental cognitive lapse in how LLMs operate. That leaves only one option not reliable but more reliable nevertheless: Human review and oversight. Possibly two of them one after the other. Everything else is snake oil but at that point, you also realize that promised productivity gains are also snake oil because reading code and building a mental model is way harder than having a mental model and writing it into code.
- raincole 5mo ago
  Don't let the perfect be the enemy of the good. Of course we know the AGENTS.md and skills aren't 100% effective. But no, it doesn't mean that they're 0% effective.
- chaostheory 5mo ago
  I can see why this would seem to be “snake oil” logically. However, this approach does work in reality. Your comment just shows that you seem inexperienced with using generative AI.
- vdelpuerto 4mo ago
  Agree. Human review and iteration. Hooks to gate certain decisions you dont want to happen again, like functional scars.
- cortesoft 5mo ago
  Everything you say is all possible, and in theory I agree with you. However, I have been using spec-kit (which is basically this style of AI usage) for the last few months and it has been AMAZING in practice. I am building really great things and have not run into any of the issues you are talking about as hypotheticals. Could they eventually happen? Sure, maybe. I am still cautious. But at some point once you have personally used it in practice for long enough, I can't just dismiss it as snake oil. I have been a computer programmer for over 30 years, and I feel like I have a good read on what works and what doesn't in practice.
koliber 5mo ago
Lately I keep hearing the same thing over and over: the things that are good for managing a team of devs are good for LLMs. Good test cases. Clear and concise documentation. CI/CD. Best practices and onboarding docs. Managing LLMs is becoming more and more similar to managing teams of people.
- tempoponet 5mo ago
  Similarly, the agentic coding success stories are from orgs that had all of these things out of the gate.
  - theshrike79 4mo ago
    Or had the sense to build the guidelines without trying to rely on writing fanfiction to guide the LLM.
- theshrike79 4mo ago
  Yep, I've been saying this for about a year now. Actually gave a presentation on this internally with this exact anecdote :D There are so many bad analogies I could use to describe it, but they're all bad so I won't try.
dmitrijbelikov 5mo ago
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lacymorrow 5mo ago
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cortesoft 5mo ago
What makes this better/different than spec-kit? It seems to have a very similar philosophy. I wonder if they could work together? Or would they just be duplicative? https://github.com/github/spec-kit https://github.com/github/spec-kit
- rTX5CMRXIfFG 4mo ago
  Nothing, they’re the same garbage for developers who can’t be bothered to mindfully use AI when writing code, and then complain about mass layoffs
stellalo 5mo ago
> A skill is a markdown file with frontmatter that gets injected into the agent’s context when the situation calls for it. When the LLM decides that the situation calls for it > It is a workflow: a sequence of steps the agent follows, with checkpoints that produce evidence, ending in a defined exit criterion. A sequence of steps the LLM can decide to follow
- lionkor 5mo ago
  Well, to be fair, in e.g. Codex you can invoke a skill directly, with $my-skill, and this WILL lead to the skill being injected into the context. At that point, the LLM follows the skill as well as it follows any other part of the prompt, instructions, or context.
- sharperguy 5mo ago
  Skills are often invoked imperatively by the user. In cases where they are intended to be used directly by the LLM, it would be included somewhere else in the context. E.g: ``` After implementing the feature, read the testing skill for instructions on how to test. ```
  - forlorn_mammoth 4mo ago
    how do you guarantee that the LLM follows an instruction given imperatively by the user? It probably will, but this is not guaranteed behavior. Likewise, _how_ it follows that instruction is non-deterministic. it's turtles all the way down.
    - sharperguy 4mo ago
      Nobody is arguing it's guaranteed. This is why you never give an LLM access to any essential infrastructure. Make sure everything it does can be undone. Double check when guarantees are required.
    - xboxnolifes 4mo ago
      You isn't gaurentee it any more than you can guarantee your prompt gives the output you want. Skills are just prompt templates.
tariky 5mo ago
What is difference between superpowers and this? I use superpowers for several months now and it really does help. But still 90/10 rule applies, 10% of time it will produce stupid decision. So always check spec.
openclawclub 5mo ago
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ColinEberhardt 5mo ago
Agents Skills are built upon “Five design decisions [that] are the load-bearing ones” And Open Design (HN front page yesterday) is supported by “Six load-bearing ideas” The similarities in the way these prompt libraries are documented doesn’t feel coincidental.
scotty79 5mo ago
> Workflows are agent-actionable; essays are not. The same is true for human teams. If your team handbook is 200 pages, no one reads it under time pressure. Agents do read that. And actually remember it. Because it's tiny with other things you are cramming into their context.
Lio 5mo ago
“A senior engineer’s job is mostly the parts that don’t show up in the diff.” Agent Skills is Addy’s attempt to kill that job too. Cheers Addy. :P
luodaint 5mo ago
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rafaelmn 5mo ago
> It’s people accepting plausible-sounding justifications for skipping the parts they don’t feel like doing. WTF ? Almost always this was "skipping the parts because the deadline was 2 weeks ago". The "I don't feel like it" rationalizations are maybe 20% ? Unless deadlines are rationalizations too ?
shruubi 5mo ago
Am I the only one who looks at guys like Addy Osmani and Steve Yegge who before LLM's had a good reputation and since then get the feeling they are cashing that reputation in to ride the LLM hype-cycle? Or is it just a matter of professional tech talking heads moving from writing books and giving conference talks about good engineering practices to talking about the new hot topic that sells books and conference tickets?
simianwords 5mo ago
The fundamental problem with agent skills is that it doesn’t have a hook to do one time installation. An agent can’t just be a prompt. It also has to have some way to do initial set up work. If I have an agent skill to look up prices of stocks, maybe I need to set up some tools and authentication first. There’s no way to express this!
hansmayer 5mo ago
What skills mate, this is simply text files attempting to narrow down the specs, hoping that this will help the "AI" make less mistakes. But it is still crap, because, <drum-rolls> - it still depends on how this fits into the overall statistical model which changes with every prompt, etc... Please stop peddling this bullshit, it does not work!
hansmayer 5mo ago
Why does it feel like it was AI-written ?
Trusteando 5mo ago
Design a test to verify that the harness keeps the rider on the horse. Parameterize it by context size.
jedisct1 5mo ago
Agent Metaskills: https://swival.dev/pages/metaskills.html https://swival.dev/pages/metaskills.html
karinakarina3 5mo ago
Another example of agent skills that give AI agents access to bitdrift's mobile observability platform for full-fidelity agentic investigations -- https://bitdrift.ai/ https://bitdrift.ai/
robeym 4mo ago
A far better approach is being precise with your prompts and if you find a new model has any bad habits, address it specifically in your AGENTS.md and go on your way. If you want to throw in slop promts, go ahead and add a massive AGENTS.md your employer gave you. People waste too much time on this stuff. The next version could totally change how the model processes your agents.md. Get good at promting, use agents.md as a minimal model annoyance fixer, and reset it often (every major release)
DeathArrow 4mo ago
Things is we have an enormous amount of skill frameworks (this, GSD, spec-kit, superpowers, Compound Engineering etc) claiming to help with agentic coding. And agents now got better builtin skills than they used to. Who will have the time to A/B test all?
kushalpatil07 4mo ago
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m3kw9 4mo ago
I'm surprised these "elite" engineers are still talking about Claude, most engineers that really use this stuff have already switched to Codex.
m3kw9 4mo ago
Most skills will also be deprecated once LLM's get updated to include these skills in their training.
RedsonNgwira 4mo ago
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standardUser 4mo ago
> It produces code, declares victory, and moves on. Not when I'm in charge. It proposes changes based on my detailed instructions, I review the proposed changes, only then do I have it implement code, and then I review it again. I understand my AI agent would prefer a quicker way but for the meantime, I'm still the one in charge.
- onlyrealcuzzo 4mo ago
  I think you're saying the same thing OP said. The point is, their default behavior is to ship crap fast. You have a process to handle that. So does OP.
alfiedotwtf 4mo ago
Isn’t this what Mixture-of-Experts is but at a higher scale?

Agent skills are ways of turning over our means of (software) production to our employers, while making ourselves obsolete at the same time. In the recent past, a (software) professional had to be continuously employed by their employer to maintain access to their professional skills. By transferring our skills into AI agent skills, we are basically giving away that privilege. In the near future, our employers might feel they don't need our skills anymore because it has already been captured by the AI agents. Somebody with a better grasp of economic history should be able to explain this using the analogy of what happened during industrial revolution and how the workers got screwed over.

cavisne 4mo ago

The problem with all these skill frameworks is when you are deep enough into AI coding to write one - your brain just cannot handle actually putting effort into it. These are all written by AI, and the authors skim read them. It’s better to do the maybe 2 hours of human effort the authors put into them yourself for your own workflow.

dhr_uvi 4mo ago

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saluc28 5mo ago

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encoderer 5mo ago

I adopted a couple of these, the api design and ui testing ones have been particularly helpful.

y-curious 5mo ago

Thanks for this, going to steal a lot of this. I would install your plugin, but I worry about being able to delete it later. I also think that each one of these is better served customized to a developer. That said, I'm still going to grab some of these, thanks!

bvirkler 5mo ago
A plugin is just a set of files, right? why wouldn't you be able to delete it later?

ElijahLynn 5mo ago

I've been using Agent Skills on a new side project and I'm really impressed so far! It really holds my hand a lot of the way and really lets me focus on developing a product instead of figuring out how to build it. I get to focus much more energy on high level architecture and product design. Very grateful for this repository and everyone who contributed to it!

CharlesW 5mo ago

From an SEO/LLMO perspective, the discoverability of these skills will be difficult without a rename: https://agentskills.io/ https://agentskills.io/ If Addy reads this, how do you pitch this vs. Superpowers? https://github.com/obra/superpowers https://github.com/obra/superpowers

consumer451 5mo ago
I would love to know how many people are actually using superpowers. I showed up on the agentic dev scene prior to superpowers, and I am getting concerned that >50% of my self-rolled processes are now covered by superpowers. I no longer trust gh stars, can anyone chime in? Is superpowers now truly adopted? If it is truly valuable, why hasn't Boris integrated the concepts yet?
- nullstyle 5mo ago
  I just removed superpowers from my own setup. In my opinion, given the quality of the planning modes in both claude code and codex, superpowers was really just slowing things down and burning more tokens than vanilla.
  - consumer451 5mo ago
    Thank you for the data point. To give back as much as I can, I use the two built-in CC review processes when appropriate. But, those only do "is this PR good code?" Far too late did I finally roll my own custom review skill that tests: "does this PR accomplish what the specs required?" If I could ask for one more vanilla CC skill, it might be that. However, maybe rolling your own repo-aware skill via prompt is better?
  - horsawlarway 5mo ago
    anecdata, but I ended up in the same spot. I used superpowers - but it burns waay more tokens for basically the same outcome as a single line that states "Please do planning and ask any required questions before implementing. [my prompt]" On the latest models and with a decent harness, the planning modes are quite good, and the single sentence telling it to ask you questions lets the model pick the right thing to ask about, instead of wasting a bunch of time/tokens on predefined skills that try to force basically the same result. It does introduce a second set of required interactions, but you can have another agent be your "questions answerer" if you need it (result quality goes down a bit vs answering myself, but still quite good, especially if you spend a bit of time on the answerer prompt) Basically - things are moving fast enough I'm not convinced buying into superpowers/agentskills/[daily prompt magic beans]/etc tooling really makes sense. I'd stick to the defaults in the harness for most cases, and then work on being clear with the ask.

stevenpetryk 5mo ago

[dead]

gosukiwi 5mo ago

I wonder how does this compare to superpowers

senko 5mo ago

> This isn’t a coincidence. It’s the same SDLC every functioning engineering organisation runs, just in different vocabulary. [...] Amazon calls it the working-backwards memo and the bar raiser. Every healthy team has some version of this loop. This (sdlc == working backwards & bar raiser) is so horribly wrong, that I hope this was an LLM hallucination. In general, I'm starting to see these agent scaffolding systems as an anti-pattern: people obsess over systems for guiding agents and construct elaborate rube-goldberg machines and then others cargo-cult them wholesale, in an effort to optimize and control a random process and minimize human involvement.

BOOSTERHIDROGEN 5mo ago
This is how similarly we collectively approach Taylorism, isn't it? However, the world favors capitalism, of which Taylorism becomes a handy scaffolding.
yks 5mo ago
The problem is it’s so rarely A/B tested, definitely not at scale. An engineer, who writes all these my-workflow-but-for-agents skills, proceeds to get the good outcome, while also seeing affirmations that the agent did follow the prescribed processes - that is considered a victory. In reality the outcome could’ve been just as good if they fed Claude a spec + acceptance criteria, or even a basic prompt for the simpler tasks.
- AndyNemmity 5mo ago
  Yeah, I Blind A/B test everything, and a lot. But I don't expect anyone to every use my stuff. It's complicated as hell. But it's for me, and it works without me having to remotely think about the complexity. I love that.
PleasureBot 5mo ago
All of these articles about setting up the perfect agent environments with skills, plugins, MCP servers, markdown files, etc. etc. reminds me so much of the culture around setting up the perfect "productivity stack". You need the perfect note-tacking app, ticketing app, calendar integrations, yada yada before you can really do anything meaningful. The reality is that you're going to get beat by someone with a few things written down on a piece of paper who is just getting stuff done.

gavmor 5mo ago

Naming things is such a hard problem that many devs don't even bother trying. That being said, this post is full of reasonable assertions, so I'm looking forward to experimenting with this... whatever it is.

fragmede 5mo ago
Wait, shit, are people using LLMs to name things now? I'm definitely out of a job then!
- kigiri 5mo ago
  Naming things is my principal use for AI, I don't always pick a name from the suggested ones but it sure help me find better ones.
- gavmor 4mo ago
  I'm notorious for taking poetic license with naming—that's how we end up with `class Escutcheon`, or variables `recto` and `verso` where applicable in eg PDF generation. But as much pleasure as I derive from novelty and specificity, my colleagues have oft expressed perplexity—whereas the terms which LLMs produce hew closer to the manifold (by definition!) and raise fewer eyebrows. So, it has its turn.

turlockmike 5mo ago

The best way to prompt an LLM is to describe the outcome you want, that's it. They are trained as task completers. A clear outcome is way better than a process. If the LLM fails, either you didn't describe your outcome sufficiently or is misinterpreted what you said or it couldn't do it (rare). Common errors should be encoded as context for future similar tasks, don't bloat skills with stuff that isn't shown to be necessary.

alexjurkiewicz 5mo ago
I agree that many skills are overblown and unnecessary. But there's a lot of value in giving AI the right process. See how much more effective Claude can be for moderate or large changes when using the superpowers skill.
peab 5mo ago
a skill is just reusuable/shareable context. It's just text, really. It's useful for things like documentation on how to use an API (this works better than MCP in my opinion), or a non consensus way of doing something. For example, you can use remotion to generate video. There are useful remotion skills that allow you to reliably generate specific types of videos. Captions of a certain style, for example.
tecoholic 5mo ago
If there is anything we have learned in decades of Software engineering, it's "A clear outcome" is not easy to describe. In many cases, it's impossible unless people from 4 different domains collaborate. That's why process matters. It allows for software to be built is a "semi-standardized" way that can allow iterations to get us closed towards the expected outcome, that might emerge over time. Yes, not everything I use LLMs for going to have the same level of ambiguity or complex requirements. Optimizing by choosing to skip over parts of the process is exactly Addy is talking in this article.
stingraycharles 5mo ago
> The best way to prompt an LLM is to describe the outcome you want, that's it. They are trained as task completers. A clear outcome is way better than a process. This is not true for anything complex. They’re instruction followers, of which task completion is just one facet. They’re also extremely eager to complete tasks without enough information, and do it wrongly. In the case of just describing task completion, despite your best efforts, there are always some oversights or things you didn’t even realize were underspecified. So it helps a lot to add some process around it, eg “look up relevant project conventions and information. think through how to complete the task. ask me clarifying questions to resolve ambiguities. blah blah”. This type of prompt will also help with the new Opus 4.7 adaptive thinking to ensure it thinks through the task properly.

zmmmmm 5mo ago

I was surprised how long some of these skills are. They are pages and pages long with tables and checkbox lists and code examples, etc. Curious how normal that is - it would only take a couple of these to really fill the context alot.

tecoholic 5mo ago
I have written zero skills, so not sure how normal it is. I counted the words in couple of them and they seem to be around 2k range. So 5 skills would be around 10K. Even at a small LLM context of 128k, that's still around 10%. And for a 1M context window like the big ones, it barely registers.
sergiotapia 5mo ago
I reviewed the line counts of my own project skill files, and the top 3 I have are: 805 lines 660 lines 511 lines Maybe I am _too_ conservative here. Lots to explore.
- mohamedkoubaa 5mo ago
  No, you aren't.
gwerbin 5mo ago
I quickly skimmed and it looks like at least a few of them are intended to be more like system prompts for a tightly scoped sub agent than a skill as such. I agree, I wouldn't want to use a lot of of these in a longer-running work session. I have been successful with short and focused skills so far. I treat them as a reusable snippet of context, but small ones. For example a couple of paragraphs at most about how to use Python in my project and how to run unit tests. I also have several short "info" skills that don't actually provide the agent instructions, they merely contain useful contextual information that the agent can choose to pull in if needed. Even having too many skills can be an issue because the list of skill names and their descriptions all end up in the context at some point.
umeshunni 5mo ago
> it would only take a couple of these to really fill the context alot. Only skill front-matter (name, description, triggers etc) are loaded within context by default, so this isn't likely to happen without 1000s of skills.

AndyNemmity 5mo ago

This is why I created the /do router, to route to all skills. I also have anti rationalization, progressive context discovery etc. I only make it for me, so it's a bit complex and targeted towards me, and what I do, but it's pretty easy to adjust things. https://github.com/notque/vexjoy-agent https://github.com/notque/vexjoy-agent Working on reading through Agent Skills, it seems we've converged on a lot of the same points, and I've never seen it, so trying to get an understanding of it. Edit 1: I don't like all the commands. I just rely on a single router to automatically decide what I want, and that feels like the most reasonable way to me to communicate with it. I don't want to remember things. And that's the way for me to scale the number of skills and activities. I don't have to think about them. Edit 2: We have very different routers. https://github.com/addyosmani/agent-skills/blob/f504276d8e074912f4763e6163b436a4ffc74d0d/skills/using-agent-skills/SKILL.md?plain=1#L2 https://github.com/addyosmani/agent-skills/blob/f504276d8e07... vs https://github.com/notque/vexjoy-agent/blob/main/skills/do/SKILL.md https://github.com/notque/vexjoy-agent/blob/main/skills/do/S... I personally wouldn't call theirs an intelligent router. They are dancing between a few different skills. We have extremely different setups there. But of course, I'm using way more context to get it done. I'm even sending it out to Haiku to build the route choices. I choose to use tokens to make things better for myself, not everyone would make the same choice, so I certainly see why they are using a few skills, and composing them. Edit 3: This is much easier for a user to wrap their head around because there's much less. I am only focused on the best improvements I can make that show value for my use cases. This is straight foward to reason about. This seems like a nice way to get the best concepts for people trying to understand them. I commend them for a clean, simple approach. Edit 4: Yeah, I think there are some things I can learn from them which is always good. I especially like simple decisions like collapsing the install details for each harness in the readme. I'm going to read over the entire thing and look for opportunities to improve my stuff. We are all working together, learning, testing, building, trying to find the best way to implement things.

codemog 5mo ago

Everyone who writes this kind of stuff skips the boring parts: science and engineering. Yep, benchmarks, comparisons of with/without, samples of generated code with/without. This kind of stuff matters, and you may be making your agent stupider or getting worse results without real analysis. Also this prose reads like the author has drunk the Google kool-aid and not much else.

ai_fry_ur_brain 5mo ago

Cant wait for everyone to realize they've wasted a year + messing with agents and experiencing a feeling of psuedo productivity.

wahnfrieden 5mo ago
You haven’t made money from their use yet?
pantheragmb 5mo ago
I couldn't agree more, just because I know I already wasted months and pulled the plug :D
nothinkjustai 5mo ago
You’ll get downvoted for this hearsay!
- footy 5mo ago
  I think you mean heresy. But maybe I don't get the reference you're making when you say hearsay
  - IncRnd 5mo ago
    Hearsay is a rumor or something that can't be verified.
    - footy 5mo ago
      I'm aware.
  - bot403 5mo ago
    I'm wondering if there are anti-ai bots trolling the boards. Look at all the usernames of the negative AI posts. Or maybe the only people left opposing AI are so hardcore against it they form their identity (username) around it

cpharsh410 5mo ago

[flagged]

dmix 5mo ago

I've tried these larger agent skillsets in the past and felt it was a waste of time because it was just doing too much. Just like vim it's often better to pick and choose from the community instead of installing skills like they are an IDE. Skills are way too personal because every dev and dev team is different. So better to treat these as a reference for your own config rather than bulk install someone else's config.

sunaookami 5mo ago
Same for MCPs and system instructions, there are a lot of people that just install everything without understanding it, cluttering their context, wasting >50k tokens for these tools they don't need and then complain that they need to pay >100$ per month because they reach their limits too fast.

Amber-chen 5mo ago

[dead]

thatmf 5mo ago

Why are people so excited to put themselves out of a job? Not that these or any "skills" will do that, but just- in principle. This is like alienation from labor at scale.

clapthewind 5mo ago
Some people are playing the global optimization game; a world where anyone can have any (production grade) software they want.
hibikir 5mo ago
Because we've been automating large parts of our former jobs for decades. Otherwise we'd all be trying to build things in the least efficient way possible to maximize how long the job takes, which IMO isn't a great idea. Humans have been minimizing how much work is needed to get a certain level of output for as long as we can track. It's civilization. Should we go back to farming by hand with hoes, to maximize labor used? Go back to streetlights that are individually lit? The society that falls behind on automation becomes poorer, and eventually just dies, as even the people born there tend to choose to leave to higher productivity places. It happened to eastern europe, it happens to the Amish. To any poor society which gets emigration. Doing more with less has always been exciting.
dewey 5mo ago
Because usually the people who lose their jobs are people who do not adapt to the market. Right now it's not clear in which direction everything is involving and that's why people experiment with handing all their data to random agents, figuring out how to store and access context, re-use prompts and other attempts to harness this tech. Most of these will maybe be useless in a year as they might be deeply integrated into the next wave of models but staying on top of the development has always been part of the fun of working in this field.
- kiba 5mo ago
  People are building bots to do the most legible thing possible which is feature in X amount of time. But it doesn't matter if the bottleneck is human thinking time required to output quality code rather than X amount of code written.

konaraddi 5mo ago

There’s so many ways, many redundant, to set up agents for software development that beyond personal/team/org needs+tastes, I need to look into setting up some benchmarks to evaluate what set up is optimal or whether the differences are even worth it.

SudheerTammini 5mo ago

Recently I have got an access(enterprise)to the latest ChatGPT module with an ability to write skills to automate repeatable taks. Without any prior knowledge I just started tinkering and now after creating and testing multiple skills in real business environment I can confidently say writing a good skill is a skill itself. As the author mentioned it's not an essay but a specific instructions sets organised in steps and in a concise manner.

theahura 5mo ago

I really wish he wouldn't use AI to write his posts. It would be faster to just post the prompt he used to write the article

petesergeant 5mo ago
I wish this fucking meme of "post the prompt" would die. Very little work is one-shotted, very little has a singular "the prompt", most is iterated until it's close to the vision of what the author actually set out to write.
- rossant 5mo ago
  Exactly. Glad to see someone else articulate this so clearly.

panavm 5mo ago

[flagged]

wg0 5mo ago

Snake oil. Good to read for sure. Seems all plausible too. But snake oil nevertheless. Here's why: The slot machine can drop any hard requirement that you specifically in your AGENTS.md, memory.md or your dozens of skill markdowns. Pretty much guaranteed. These harnesses approaches pretend as if LLMs are strict and perfect rule followers and the only problem is not being able to specify enough rules clearly enough. That's fundamental cognitive lapse in how LLMs operate. That leaves only one option not reliable but more reliable nevertheless: Human review and oversight. Possibly two of them one after the other. Everything else is snake oil but at that point, you also realize that promised productivity gains are also snake oil because reading code and building a mental model is way harder than having a mental model and writing it into code.

raincole 5mo ago
Don't let the perfect be the enemy of the good. Of course we know the AGENTS.md and skills aren't 100% effective. But no, it doesn't mean that they're 0% effective.
chaostheory 5mo ago
I can see why this would seem to be “snake oil” logically. However, this approach does work in reality. Your comment just shows that you seem inexperienced with using generative AI.
vdelpuerto 4mo ago
Agree. Human review and iteration. Hooks to gate certain decisions you dont want to happen again, like functional scars.
cortesoft 5mo ago
Everything you say is all possible, and in theory I agree with you. However, I have been using spec-kit (which is basically this style of AI usage) for the last few months and it has been AMAZING in practice. I am building really great things and have not run into any of the issues you are talking about as hypotheticals. Could they eventually happen? Sure, maybe. I am still cautious. But at some point once you have personally used it in practice for long enough, I can't just dismiss it as snake oil. I have been a computer programmer for over 30 years, and I feel like I have a good read on what works and what doesn't in practice.

koliber 5mo ago

Lately I keep hearing the same thing over and over: the things that are good for managing a team of devs are good for LLMs. Good test cases. Clear and concise documentation. CI/CD. Best practices and onboarding docs. Managing LLMs is becoming more and more similar to managing teams of people.

tempoponet 5mo ago
Similarly, the agentic coding success stories are from orgs that had all of these things out of the gate.
- theshrike79 4mo ago
  Or had the sense to build the guidelines without trying to rely on writing fanfiction to guide the LLM.
theshrike79 4mo ago
Yep, I've been saying this for about a year now. Actually gave a presentation on this internally with this exact anecdote :D There are so many bad analogies I could use to describe it, but they're all bad so I won't try.

dmitrijbelikov 5mo ago

[dead]

lacymorrow 5mo ago

[flagged]

cortesoft 5mo ago

What makes this better/different than spec-kit? It seems to have a very similar philosophy. I wonder if they could work together? Or would they just be duplicative? https://github.com/github/spec-kit https://github.com/github/spec-kit

rTX5CMRXIfFG 4mo ago
Nothing, they’re the same garbage for developers who can’t be bothered to mindfully use AI when writing code, and then complain about mass layoffs

stellalo 5mo ago

> A skill is a markdown file with frontmatter that gets injected into the agent’s context when the situation calls for it. When the LLM decides that the situation calls for it > It is a workflow: a sequence of steps the agent follows, with checkpoints that produce evidence, ending in a defined exit criterion. A sequence of steps the LLM can decide to follow

lionkor 5mo ago
Well, to be fair, in e.g. Codex you can invoke a skill directly, with $my-skill, and this WILL lead to the skill being injected into the context. At that point, the LLM follows the skill as well as it follows any other part of the prompt, instructions, or context.
sharperguy 5mo ago
Skills are often invoked imperatively by the user. In cases where they are intended to be used directly by the LLM, it would be included somewhere else in the context. E.g: ``` After implementing the feature, read the testing skill for instructions on how to test. ```
- forlorn_mammoth 4mo ago
  how do you guarantee that the LLM follows an instruction given imperatively by the user? It probably will, but this is not guaranteed behavior. Likewise, _how_ it follows that instruction is non-deterministic. it's turtles all the way down.
  - sharperguy 4mo ago
    Nobody is arguing it's guaranteed. This is why you never give an LLM access to any essential infrastructure. Make sure everything it does can be undone. Double check when guarantees are required.
  - xboxnolifes 4mo ago
    You isn't gaurentee it any more than you can guarantee your prompt gives the output you want. Skills are just prompt templates.

tariky 5mo ago

What is difference between superpowers and this? I use superpowers for several months now and it really does help. But still 90/10 rule applies, 10% of time it will produce stupid decision. So always check spec.

openclawclub 5mo ago

[flagged]

ColinEberhardt 5mo ago

Agents Skills are built upon “Five design decisions [that] are the load-bearing ones” And Open Design (HN front page yesterday) is supported by “Six load-bearing ideas” The similarities in the way these prompt libraries are documented doesn’t feel coincidental.

scotty79 5mo ago

> Workflows are agent-actionable; essays are not. The same is true for human teams. If your team handbook is 200 pages, no one reads it under time pressure. Agents do read that. And actually remember it. Because it's tiny with other things you are cramming into their context.

Lio 5mo ago

“A senior engineer’s job is mostly the parts that don’t show up in the diff.” Agent Skills is Addy’s attempt to kill that job too. Cheers Addy. :P

luodaint 5mo ago

[dead]

rafaelmn 5mo ago

> It’s people accepting plausible-sounding justifications for skipping the parts they don’t feel like doing. WTF ? Almost always this was "skipping the parts because the deadline was 2 weeks ago". The "I don't feel like it" rationalizations are maybe 20% ? Unless deadlines are rationalizations too ?

shruubi 5mo ago

Am I the only one who looks at guys like Addy Osmani and Steve Yegge who before LLM's had a good reputation and since then get the feeling they are cashing that reputation in to ride the LLM hype-cycle? Or is it just a matter of professional tech talking heads moving from writing books and giving conference talks about good engineering practices to talking about the new hot topic that sells books and conference tickets?

simianwords 5mo ago

The fundamental problem with agent skills is that it doesn’t have a hook to do one time installation. An agent can’t just be a prompt. It also has to have some way to do initial set up work. If I have an agent skill to look up prices of stocks, maybe I need to set up some tools and authentication first. There’s no way to express this!

hansmayer 5mo ago

What skills mate, this is simply text files attempting to narrow down the specs, hoping that this will help the "AI" make less mistakes. But it is still crap, because, <drum-rolls> - it still depends on how this fits into the overall statistical model which changes with every prompt, etc... Please stop peddling this bullshit, it does not work!

hansmayer 5mo ago

Why does it feel like it was AI-written ?

Trusteando 5mo ago

Design a test to verify that the harness keeps the rider on the horse. Parameterize it by context size.

jedisct1 5mo ago

Agent Metaskills: https://swival.dev/pages/metaskills.html https://swival.dev/pages/metaskills.html

karinakarina3 5mo ago

Another example of agent skills that give AI agents access to bitdrift's mobile observability platform for full-fidelity agentic investigations -- https://bitdrift.ai/ https://bitdrift.ai/

robeym 4mo ago

A far better approach is being precise with your prompts and if you find a new model has any bad habits, address it specifically in your AGENTS.md and go on your way. If you want to throw in slop promts, go ahead and add a massive AGENTS.md your employer gave you. People waste too much time on this stuff. The next version could totally change how the model processes your agents.md. Get good at promting, use agents.md as a minimal model annoyance fixer, and reset it often (every major release)

DeathArrow 4mo ago

Things is we have an enormous amount of skill frameworks (this, GSD, spec-kit, superpowers, Compound Engineering etc) claiming to help with agentic coding. And agents now got better builtin skills than they used to. Who will have the time to A/B test all?

kushalpatil07 4mo ago

[flagged]

m3kw9 4mo ago

I'm surprised these "elite" engineers are still talking about Claude, most engineers that really use this stuff have already switched to Codex.

m3kw9 4mo ago

Most skills will also be deprecated once LLM's get updated to include these skills in their training.

RedsonNgwira 4mo ago

[flagged]

standardUser 4mo ago

> It produces code, declares victory, and moves on. Not when I'm in charge. It proposes changes based on my detailed instructions, I review the proposed changes, only then do I have it implement code, and then I review it again. I understand my AI agent would prefer a quicker way but for the meantime, I'm still the one in charge.

onlyrealcuzzo 4mo ago
I think you're saying the same thing OP said. The point is, their default behavior is to ship crap fast. You have a process to handle that. So does OP.

alfiedotwtf 4mo ago

Isn’t this what Mixture-of-Experts is but at a higher scale?