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Comment by simonw | Hacker News Reader

I think I made good call on Skills.

They were only announced in October and they've already been ported to Codex and Gemini CLI and VS Code agents and ChatGPT itself (albeit still not publicly acknowledged there by OpenAI). They're also used in Cowork and are part of the internals in Fly's new Sprites. They're doing extremely well for an idea that's only three months old!

This particular post on Cowork isn't some of my best work - it was a first impression I posted within a couple of hours of release (I didn't have preview access to Cowork) just to try and explain what the thing was to people who don't have a $100+/month Claude Max subscription.

I don't think it's "unhealthy" for me to post things like this though! Did you see better coverage of Cowork than mine on day one?

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> But none of that is healthy for you and me.

I read that as it's not healthy to constantly follow the day one posts about every iteration of brand new technology in order to try and see how to incorporate it into your workflow in a rapidly evolving manner.

It's not an attack on your article or your habits, it's an accurate indictment of chronically consuming probably short-lived hype instead of practicing craft and the use of hardened tools, much like watching certain programmers on youtube to know about the latest frontend library instead of just working on something with versatile, generalizable, industry-relevant tools

Not sure we're you heard this.

Can be a stupid advice.

The ai field moves fast, what's wrong being an early adopter and experimenting around with it?

Someone has to do it.

And tbh skills are an easy to use concept to make Claude faster and the context smaller.

You made the right call. Skills were added to Antigravity and I immediately started creating and using them. I never used custom MCP servers, but skills were immediately obvious to me.

An example: I made a report_polisher skill that cleans some markdown formatting, check image links, and then uses pandoc to convert it to HTML. I ask the tool itself created the skill, then I just tweaked it.

How is the fidelity of something like this? It seems like it would randomly fuck it up once in a blue moon. Is that not the case? For your use case I don't understand why you would want an AI involved at all.

Skills may have have code attached to them, so in this case the formatting and converting is all code.

The value of skills is that they are attached to the context of an LLM for few tokens, and the LLM activates one when it feels that it relevant (and brings it into context). It's a chepear alternative to having a huge CLAUDE.md (or equivalent) file.

Fascinating thank you.

Spot on. The value of skills is using a much smaller context to improve the quality of the output.

This is plainly obvious to anyone who understands how these LLMs work.

Please do open-source your skill and blog about it. Also, would like to hear from your experience after a few months of use. Like - how many times did you use the skill, did you run into some problems later (due to some unexpected thing in the markdown), did the skill generalize - or do you have to make tweaks for particular inputs.

@brailsafe has accurately captured where I am coming from.

I want more blogs/discussion from the community about the existing tools.

In 3/6 months, how many skills have you written? How many times have you used each skill? Did you have edit skills later due to unseen corner cases, or did they generalize? Are skills being used predominantly at the individual level, or are entire teams/orgs able to use a skill as is? What are the usecases where skills are not good at? What are the shortcomings?

(You being the metaphorical HN reader here of course.)

HN has always been a place of greater technical depth than other internet sites and I would like to see more of this sort of thing on the front page along with day one calls.

I'd love to see answers of those questions too, especially the team ones.

Personally the skills that I have found most useful that I've written myself are these:

- uv-tdd - run a TDD loop on a Python project via uv: https://github.com/simonw/skills/blob/main/uv-tdd/SKILL.md

- setup-to-pyproject - migrate a setup.py Python project to pyproject.toml in the way I prefer https://github.com/simonw/skills/blob/main/setup-to-pyprojec...

- datasette-plugins: everything an LLM needs to write a new Datasette plugin https://github.com/datasette/skill/blob/main/SKILL.md

You did make a good call on skills.

Anything that lets us compose smaller tasks into larger ones effectively is helpful. That’s because self-attention (ie context) is still a huge limiting factor.

As someone who uses these tools a lot, and who sits on the bleeding edge everyday, I agree with you.

MCP got a ton of use out of the gate. People were fawning over it for the first few months, and we can see how well that hype survived contact with hardcore engineers.

There was a funny YouTube which came out immediately after the release where Claude rm -rf all dude's files o_O

https://www.youtube.com/watch?v=_6C9nMvQsGU

YOLO? More like LOLOL

you have to be crazy to run claude in YOLO mode outside of a constrained environment such as a docker container

There's an awful lot of people running these tools in YOLO mode.

https://embracethered.com/blog/posts/2025/the-normalization-...

The fact you could see in the video what was going on for several minutes before the guy noticed it…

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