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- I commit them to git(so complete team leverages them)., each repo has kind of different skills and the skills are the ones which I update at least twice a week. I’ve skills on how to add instrumentation , debug, code, code review, tech design review etc. I found most of the skills I find on skills.sh are not very useful for me., but I browse occasionally to get some inspiration. One more paradigm I’m seeing good results on adding new skills is ‘how to do X’, for instance ‘how to add logs’., “how to review code” etc., if i’m not able to frame it that way I don’t think it’s a good use case for me to add that skill to the llm arsenal.
Another thing i discovered is less is more (in case of skills as well)., don’t add lots of skills., keep them very handful - I’ve got 9 skills so far (many people have 100s installed from marketplaces and plugins)
- Get them under version control. I have a git repo with my skills for software development [1]. There is an installer script that symlinks to the skills. Updating the skills on a machine is then just a matter of advancing the git repo. One of the skills comes with some bash scripts, but the rest are effectively just prompts. Putting project specific skills in projects works well.
I make sure they work by understanding every skill, reviewing pull requests, and testing the end product. The result is rarely perfect, so I am constantly tweaking the skills and how I use AI.
by gregwebs - Skills are encoding a process. The more niche the process the more useful the skill. As the process grows to a larger audience it becomes more generic and thus converges with the models knowledge. So skills are better for a smaller group of people. And similarly how it's packaged and maintained becomes specific to that group.by darren0
- I don't use any skills, what kinds of skills are people finding most useful?
For general tasks, the model seems perfectly capable of figuring out things itself, for project or environment specific tasks, I just put that information in the readme or agents.md file.
by WatchDog - First, a lot of people in thread are saying you don't need skills. This is pretty wrong. There is a lot of alpha in using any set of skills that implements SPACE (search, plan, assert, code, evaluate). See: https://open.substack.com/pub/theahura/p/agentics-using-meta...
Second, we share all of our sets of skills in a purpose built registry: https://noriskillsets.dev/ you can use any of our public skillsets from there. If you're on a team you can also sign up to get your own private registry. Makes organization much easier.
Finally, for local development, we use this CLI to manage skills (https://github.com/tilework-tech/nori-skillsets). This is a tool that lets you bundle skills into groups, and then switch between those groups. So for eg if I'm making a slide deck I'll use an admin skillset, and for coding I'll use a swe skillset, and for debugging I'll use a debugging skillset.
We do keep tinkering with our skillsets, but not very much. I don't get the need to adjust things for every model release, doesn't seem necessary for us in practice
by theahura - - I don't find skills, I create them
- Keep them organised in software repos that you install with symlinks for all coding harnesses that you have. Progressive disclosure based on the frontmatter does the rest.
- I make sure they work with AI evals. Think of them like integration tests to prove behaviour. They're useful to optimize your flows. I try to make my skills be mostly a translation between natural language and good small fast tools that they call.
- I change them as a new problem arises. Not just because.
Skills can't be eaten by model capabilities if skills represent a workflow that is custom to my team or my person.
I wrote about a good mental model in the past:
https://alexhans.github.io/posts/series/evals/building-agent...
by alexhans - I don’t find skills. I write my own skills based on things I do frequently and repeatably. I keep them version controlled locally and in GitHub, and I symlink that folder to my various agent skill folders so they all stay up to date.
I feel like downloading a bunch of skills is another one of those useless collections people make purely because they have infinite options. It’s like those collections of thousands of bookmarks you’re never going to click or pirated ebooks you’re never going to read.
It’s trivial to write your own skills with agents. The best way to use them, imo, is to make them when you have repeatable agent workflows, written to your own personal taste, and updated as your workflows change.
Here’s what I have for reference:
- Remove agent-speak from code, docs, and markdown files.
- Ask sequences of questions the way I like to be asked questions. Used instead of the question tool. This is my primary design skill as well.
- How to use jj the way I want my agent to use jj
- Dispatch subagents with 6 different sets of priorities. Those priorities are defined in the skill, so I can always dispatch all 6 of them to write or review code. Includes a template for code reviews
- Manage a local MD issue tracker for personal projects
by picklenerd - Skills are mostly snake oil, the way people use them (the aspiration to download kung foo from a celebrity).
There was a time when maybe it mattered (last year), but with good repos and good prompts today's agents can find exactly what they need without any skills.
"Skills" as developer macros can be useful, but at most those are things shared with the team (in the repo), not something you download from the internet. If you have so many skills that you feel the need to manage them, that's a code smell.
by avaer