I use skills all day, every day. One of my greatest annoyances right now is having to switch between `/` and `$` in moving between CC and codex. At one point I attempted to hack the CC TUI to accept $ but failed, I may yet return to that.
All of my skills are custom to my workflows except Contextify (more on that at the end) This extends to how I distribute them across multiple development machines.
They live in my `cli-ai-setup` repo alongside agent settings, git worktree tooling, iTerm workspace restoration (important, machines have to restart and crash sometimes), code review scripts, and machine setup guides. I use git to carry changes between machines and a setup script to symlink the skills into a shared directory that Claude Code and Codex both use.
I have a `skills-and-settings` skill specifically for deciding where new skills belong and how to make them available (project, global, application). I also have a custom `skill-create` skill that turns sessios into new skills or updates existing ones.
Importantly, I also have entire custom applications I have not yet made open source that my cli-ai-stack relies on. I do expect to distribute these so they live in their own repo and are symlinked or installed in as appropriate.
For maintenance, I've largely handled this manually and organically. When a skill is not performing, I'll use the context of the situation as the ~1 shot or pull in more examples for the ai:
This skill seems to not be performing as expected on [something].
This has happened a couple of times now use /total-recall to find similar recent situations for example [something I remember]"
Recommend updates to the skill and upon approval commit and push them...etc.
My other machines watch this repo and the symlink structure means that the updates are carried into live cli-ai sessions almost immediately.
This past week I was exploring the automatic skill improvement behavior described in the Anthropic blog guest post with their partner org. I'd previously build a "dreaming" skill that works okay and think there may be some value yet to plumb there.
For skill creation, I have a skill that reads the official skill docs for both Claude Code and Codex. This way the skills are built to handle both platforms particularities. I automatically pull those docs into local Markdown daily, so it has a regularly refreshed reference for what each tool supports.
As mentioned above, I have built Contextify (https://contextify.sh) which provides a sql database of all of my Claude Code an Codex session transcripts across all of my development machines. The skill for this (/total-recall) is the most important skill I have and I use it constantly.
All of my skills are custom to my workflows except Contextify (more on that at the end) This extends to how I distribute them across multiple development machines.
They live in my `cli-ai-setup` repo alongside agent settings, git worktree tooling, iTerm workspace restoration (important, machines have to restart and crash sometimes), code review scripts, and machine setup guides. I use git to carry changes between machines and a setup script to symlink the skills into a shared directory that Claude Code and Codex both use.
I have a `skills-and-settings` skill specifically for deciding where new skills belong and how to make them available (project, global, application). I also have a custom `skill-create` skill that turns sessios into new skills or updates existing ones.
Importantly, I also have entire custom applications I have not yet made open source that my cli-ai-stack relies on. I do expect to distribute these so they live in their own repo and are symlinked or installed in as appropriate.
For maintenance, I've largely handled this manually and organically. When a skill is not performing, I'll use the context of the situation as the ~1 shot or pull in more examples for the ai:
My other machines watch this repo and the symlink structure means that the updates are carried into live cli-ai sessions almost immediately.This past week I was exploring the automatic skill improvement behavior described in the Anthropic blog guest post with their partner org. I'd previously build a "dreaming" skill that works okay and think there may be some value yet to plumb there.
For skill creation, I have a skill that reads the official skill docs for both Claude Code and Codex. This way the skills are built to handle both platforms particularities. I automatically pull those docs into local Markdown daily, so it has a regularly refreshed reference for what each tool supports.
As mentioned above, I have built Contextify (https://contextify.sh) which provides a sql database of all of my Claude Code an Codex session transcripts across all of my development machines. The skill for this (/total-recall) is the most important skill I have and I use it constantly.