Agent skills are a crucial, yet often overlooked, feature in AI development tools like Claude Code and Codex, enabling enhanced prompt context and functionality. Mastering three core types of skills can significantly improve AI agent performance and utility.
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When working with Claude Code, Codex, or any other agentic engineering
tool, one really important concept that is supported by
all these tools that you should understand and use is the
concept of agent skills. And it's easy to ignore them
because it's just a bunch of Markdown files or because setting them
up can be cumbersome, but it is worth it, in my experience.
And a couple of days ago, there was a post by someone on the
Cloud Code team, so someone from Anthropic, where he
shared the different types of skills they are using
internally because indeed, you can differentiate between different
types of skills you wanna create. They're all just Markdown files in the
though you can add a bit more. I'll get back to that.
But, of course, what's inside that Markdown file can
be quite different. Now, this image here,
and this entire post can be quite overwhelming and can lead
to not doing anything because you feel like, "Okay, if I gotta spend a
week setting up skills, I'd rather not use them at all."
offer an alternative to that in this video.
I think you can simply have three core types of skills that you
should care about and that will lead to better results.
By the way, as I mentioned, all these tool support skills,
set them up, how to actively invoke them, how to build skills for Cloud Code, for
Codex, in my respective courses. And if you wanna get those courses or get
access to all my courses, including future courses,
promotion where you can get the annual membership, which gives you full access to
all my courses as long as you have the membership for a super low price.
Link below. But regarding these skills here,
they are just Markdown files, Markdown files that
place, and the exact place depends on the tool
But in the end, they are there for prompt templates
context that can be injected into your
agentic engineering sessions. And the first type
of skill is the documentation or the
knowledge skill, I would say. Now, what do I mean by that?
Here, I'm in my academind.com project, so the project of my website,
and in there, I got a bunch of agent skills that
just kinds of documentation or
knowledge I expose to the AI agent here.
For example,
some TypeScript knowledge here, some knowledge
about more advanced TypeScript features, maybe some
newer features like the satisfies keyword, which hasn'st
been around for 10 years. Some stuff I
want the AI agent to be aware of or to be
reminded of because it might not be the first
things it's reaching for because maybe it hasn't seen as much of
that stuff in its training data. So
this really is something you could find in the official TypeScript
documentation. The thing just is that unless you
explicitly tell the agent to do so, it very likely will
not go to that official documentation.
It will not go to the TypeScript documentation.
So I rather have my own skill, and
this skill here has some metadata.
The metadata is important because the idea behind the skills is that
not all available skills are loaded into the context window every
time. Instead, just the metadata is loaded into the context window, and
then the AI agent can decide for which skill it wants
to read more depending on your prompt and your tasks you gave
it. You can also actively invoke skills
you're using, but the main idea is that the agent loads them on its own
depending on that metadata. So here I have some metadata, uh,
where I try to give the agent some
idea on when to use this skill. And therefore, that is one
type of skill that you provide extra documentation or knowledge
that the agent may not have because maybe you're also working with
some library which was not in the training data because it's
or where you know that it maybe hasn't seen a lot of about
want it to be aware of. So that's the- the first type of s- skill, I would say.
The second type of skill is behaviors,
best practices,
a- approaches, that kind of stuff.
And here, the idea really is that, of course,
when you're working on a project, you may have certain
preferences regarding code style or
regarding how some stuff should be done.
So for example, I have this clean modern React code skill,
is not so much about documenting React features, but instead about
establishing some rules the agent should follow when it's
writing React code to ensure that certain-
that- that certain antipatterns are less common, at least, because at
least for me right now, AI agents
tend to generate code that's not always the highest
quality. And you could argue whether you care about
I created a separate video on a different channel about that.
I would say it matters because code quality matters for being able
to review the code, it can have performance implications,
implications on how easy the code is to maintain or extend, so
I'd say it matters. And if you have certain behaviors or
patterns you want the agent to use, then such a
behavioral skill where you tell it how to write
good React code that you- that it should try to avoid useEffect
and how it can avoid it, that kind of skill can be interesting.
So here, it's less about providing extra
documentation, extra knowledge, but instead about instructing
behaviors. Now, what's interesting about this skill
some related files with a file with more details about
useEffect because all these skill files are
loaded lazily, as I already said, and you can, in
a skill file, reference another file like this
the references folder here, and then the AI can decide to load
that file only when it knows that it is working with useEffect, that it-
doing something with useEffect. So that here, I then have more
details about antipatterns it-... it should be aware of.
And setting up these kinds of skills can be well worth it, also
because, of course, I can copy that into any React project.
I don't have to rewrite it all the time, and it can lead to better
code there. So that's the second type of skill I would
recommend doing, and you don't have to think of all the
different patterns you might wanna describe.
Instead, just act step by step. If you see that in your
project, the AI agent is consistently doing something you don't
it to do, add a skill where you think about a good
description that increases the chance of the skill being loaded in the right
times, and then put your instructions in
So, use it to fix stuff, and over time, you'll build a skill
library with your specific, um, best practices and
behaviors you want to enforce, and you can then use
So, don't see it as that big upfront task that is super
intimidating. Instead, build that skill base, um, step by
step. Now, the third type of skill, and that's a different type of
skill, is, uh, functionality driven
skills. Thus far, we talked about documentation
specific behaviors.
Now, these agentic engineering tools like
do all kinds of stuff. They can write code obviously,
to writing code in- in projects. Since they can write code, they
can do anything on your computer. If you want, you can use them to
analyze, um, PDF documents, for example,
or I have some global skills on my system which are not
specific to just programming. Some of them are, but not all.
You could set up a skill that tells an agent how to
generate an image. Now, what do I mean by that?
Well,
there are of course various services or APIs you can use to
generate images or video with AI, something
like Fell.ai. This is not a sponsored video by the way.
There also is Replicate, and there are different services.
Now of course, if you want to generate an image,
project you need a dummy image in your website, or for something totally
different, uh, an image you wanna print
you can use these services and you could use
Codex, Claude Code, the PAI agent, which I like a lot, and
ask it to generate an image for you.
By default, it very likely will fail, because these agentic engineering
tools, they don't have image generation
But if you give them the right skill, which still is just a Markdown file,
in there, you can of course describe how to interact
third-party API to generate an image.
Now, just describing that interaction might be one way,
a step further.
Your skills can also come with scripts.
Not all need them, but here, my GenerateImage skill does.
This script is a script which, to be honest, was written by
AI. It was white-coated.
And in here, I have some- some scripts that interacts
with the Fell API, so of that image generation service.
I essentially took their documentation, put it into a prompt, and
told an AI agent to write me a tool that can
utilize or that can talk to that API by Fell to
generate images. So, a little CLI tool was written
here, a little script that can talk to that
API and generate images with different parameters and so on.
And then the Skill.md file, that file just explains how to use
that script. It points at it and it tells the agent how to
execute it, which parameters to pass, and- and so on.
And then I got the .env file here with my Fell
key. And when that script here is
invoked through bun, which is what I'm telling the AI in the Skill.md
that .env file will be loaded automatically so I don't have to
give my agent access to that key. I don't have to tell it, "Please
generate an image. By the way, here's the key." Instead,
generate an image. It will, thanks to this description, load this
skill when it needs to, and then in there, it learns that it just needs to run a
script and it doesn't need to worry about the implementation details And
that is another kind of skill that I think is
interesting, not just related to programming.
You could, of course, also have a script driven skill there,
that formats the code or I don't know.
But in general, because you can really use these agents
just generating code, and therefore that definitely is another skill category
be aware of. But yeah, as a whole, I'd say don't
overcomplicate it, but also don't sleep on it.
Instead, build your skill library step by step.
It's worth noting that, of course, there are skill registries like
skills.sh where you can browse skills built by
other people. Just two important notes.
This can be very useful, but what I would not do
is say, "Okay, I'm building a React project with Tailwind
and Better Off and I don't know, so I will search for all the
skills that could potentially be interesting there,
my project." That might be counterproductive, because you're loading
lo- more and more metadata into your context
m- some of these skills just might not
So, that is one thing to be aware of.
I would not always try to add all the skills that you could theoretically
add. Instead, you should be selective and focus on the- on the things the-
the AI consistently gets wrong or, um, where you know that
extra documentation will be needed. That's one thing.
And the other thing about these registries, of course, is you are
including skills that were written by other people.
These skills, as we learned, are just prompts.
If there is something malicious in one of these prompts,
that could be a problem. That can lead to a prompt injection
be aware of that. Now, some registries like skills.sh,
to my knowledge, do some form of scanning to kind of,
um, reduce the danger of s- uh, prompt injections, but
you're never 100% secure and that is therefore something to be aware of.
So, whenever you're using a skill written by
(laughs) It's- it's there for you to read.
Uh, take a look at it and see if there is something malicious in there.
That's just one word of caution. But yeah, other than that,
use skills. Don't feel like you need to build a super
system here. Instead, play around with them and keep these
three core types of skills in mind
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