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.
To the extent that skills are contextual guidance (for this author, this project, etc) and not just (raw) capabilities they are unlikely to be eaten by models.
I maintain all my skill files in a central location (like dotfile management) and have guix home sync it to the skill folders of various harnesses that I'm playing with (codex, pi, antigravity, Claude Code, Deepseek harness, etc). They're set up to be bidirectional links rather than read-only like the default configuration, so I can keep editing them / adding to the corpus from any harness.
This works well for skills since all harnesses expect the same format, but is more annoying for other features.
I recently completely overhauled repo’s skill setup.
I tried to control the execution of tasks performed by each project using claude.md within the project, but claude.md is only read at the beginning of each session, so it felt like the instructions weren’t being properly reflected.
So I revised the strategy to manage frequently used features in skill units. In doing so, instead of organizing skills by project, it was structured to be integrated into the general skills of the individual repo.
When skills are spread out across multiple projects and the number increases, it becomes impossible to keep track of which skills are available, so they end up not being used.
I also think that eventually, once Claude(model) advances, it will be able to replace most of the skills, so I believe registering and managing countless skills actually degrades performance.
I try to keep my collection of community skills short, usually a few established names (mattpocock, mcollina, trailsofbit). And then I check new releases (or when mattpocock published a youtube video for instance :D)
> keep them organized
For skills I wrote myself, I have my own private github repo. I use skills like /commands most of the time, so I can tell if they work straight away.
For community skills, a package manager really helps. vercel-labs/skills and withastro/rosie are good options. I also built one myself: https://github.com/osrim/ski. It has some cool features like an update command and a security scan.
We have some company-managed skills, that help coding agents find the relationships between our repos, and our conventions, architecture, and other high-level decisions. These are supposed to be portable between agents, and so distributing them is currently awkward.
We have a bootstrap script to deploy company-managed skills to each developer's "personal" skills. Hooks for codex and claude code try to refresh the skills on each startup.
I manage them as part of my dotfiles using chezmoi. A `.agents/skills/` directory + a symlink to there from `.claude/skills/`.
> Do you keep improving them over time?
In my global AGENTS.md I have a note to agents to explain any frustrations they had doing a task, and to suggest any skill/tool/AGENTS.md improvements. I am trying to keep AGENTS.md files small but still finding the balance.
>I believe skills will eventually be eating by model capabilities
a model capability is never going to fill in an unknowable blank that a custom skill (or whatever equivalent your paradigm supports) can.
a model might have the cleverness to whoami and look through the .ssh folder for keys and evidence of past connections when asked to connect to bob, but a skills file can just easily say "We connect to bob using key Z and user X." so that the operation gets done without all this nonsense needless inference as far into the future as the information is valid for.
a concise information dense skill is going to always dominate on tokens-burnt for any given task that requires insider knowledge. it simply gets rid of the entire investigative phase of work.
Agree here. My philosophy is the "general-purpose" coding agent will keep getting better and better, making skills less and less useful. And it will probably get better at a pace far greater than the customization folks can build around them via skills.
This of course is from my own experience writing code, where agents are already good at software engineering conventions. This probably doesn't hold as well for other tasks, say writing marketing copy with a unique voice
For now, I keep skills pretty minimal - single sentence prompts I send all the time, like "Remove all the slam poetry from the docs in this repo."
I also tend to share often. All skills go into a repo my team can access. No pressure, use them, riff on them, add your own - sharing and engaging on how we do the work is more important than making everyone do the work the same way to me.
What I meant by skills getting eating by models are the "general use" skills, like design critique, code review...ect
But, for custom use skills, ofc no model will be able to replace them and it's not efficient to try to do that as well. For this type of skills I create and maintain them by myself, my question was about "general use" skills, they are everywhere on the internet, how do you manage them?
Do you find any of the general use skills useful? I'm not sure I've ever used any of them, and when I've looked at them it's been some YouTuber trying to make money. That, and their Substack.
I know everyone's down on MCP, but custom-built client side MCP tools are what I find useful instead. But that's me.
https://agent-plugins.org/
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.
I maintain all my skill files in a central location (like dotfile management) and have guix home sync it to the skill folders of various harnesses that I'm playing with (codex, pi, antigravity, Claude Code, Deepseek harness, etc). They're set up to be bidirectional links rather than read-only like the default configuration, so I can keep editing them / adding to the corpus from any harness.
This works well for skills since all harnesses expect the same format, but is more annoying for other features.
I tried to control the execution of tasks performed by each project using claude.md within the project, but claude.md is only read at the beginning of each session, so it felt like the instructions weren’t being properly reflected.
So I revised the strategy to manage frequently used features in skill units. In doing so, instead of organizing skills by project, it was structured to be integrated into the general skills of the individual repo.
When skills are spread out across multiple projects and the number increases, it becomes impossible to keep track of which skills are available, so they end up not being used.
I also think that eventually, once Claude(model) advances, it will be able to replace most of the skills, so I believe registering and managing countless skills actually degrades performance.
I try to keep my collection of community skills short, usually a few established names (mattpocock, mcollina, trailsofbit). And then I check new releases (or when mattpocock published a youtube video for instance :D)
> keep them organized
For skills I wrote myself, I have my own private github repo. I use skills like /commands most of the time, so I can tell if they work straight away.
For community skills, a package manager really helps. vercel-labs/skills and withastro/rosie are good options. I also built one myself: https://github.com/osrim/ski. It has some cool features like an update command and a security scan.
We have a bootstrap script to deploy company-managed skills to each developer's "personal" skills. Hooks for codex and claude code try to refresh the skills on each startup.
> Do you keep improving them over time?
In my global AGENTS.md I have a note to agents to explain any frustrations they had doing a task, and to suggest any skill/tool/AGENTS.md improvements. I am trying to keep AGENTS.md files small but still finding the balance.
a model capability is never going to fill in an unknowable blank that a custom skill (or whatever equivalent your paradigm supports) can.
a model might have the cleverness to whoami and look through the .ssh folder for keys and evidence of past connections when asked to connect to bob, but a skills file can just easily say "We connect to bob using key Z and user X." so that the operation gets done without all this nonsense needless inference as far into the future as the information is valid for.
a concise information dense skill is going to always dominate on tokens-burnt for any given task that requires insider knowledge. it simply gets rid of the entire investigative phase of work.
This of course is from my own experience writing code, where agents are already good at software engineering conventions. This probably doesn't hold as well for other tasks, say writing marketing copy with a unique voice
For now, I keep skills pretty minimal - single sentence prompts I send all the time, like "Remove all the slam poetry from the docs in this repo."
I also tend to share often. All skills go into a repo my team can access. No pressure, use them, riff on them, add your own - sharing and engaging on how we do the work is more important than making everyone do the work the same way to me.
But, for custom use skills, ofc no model will be able to replace them and it's not efficient to try to do that as well. For this type of skills I create and maintain them by myself, my question was about "general use" skills, they are everywhere on the internet, how do you manage them?
I know everyone's down on MCP, but custom-built client side MCP tools are what I find useful instead. But that's me.
it has all the skills/docs my particular application needs
i treat it as ADRs as it helps the AI understand the parts of the system it is working on