The short version: sx treats skills, MCP server configs, slash commands, agents, hooks, and rule files as versioned packages. You define them once, push them to a vault (a local folder, a git repo, or our hosted backend), and install them where they belong. There's a lockfile so installs are reproducible, scope levels for org / team / repo / individual, and the CLI translates the same asset into the format each AI client expects.
Supported clients today: Claude Code, Cursor, GitHub Copilot, Cline, Codex, Gemini (CLI / VS Code / JetBrains / Android Studio), Kiro, claude.ai, chatgpt.com. The last two are what let non-engineering teams (marketing, legal, ops) use the same primitive instead of being locked out of the AI-assets ecosystem.
The thing I'd most like feedback on is whether the scope model is the right shape. Org → team → repo → path → individual is what's emerged from talking to ~60 teams over the last six months, but I expect bigger orgs will surface scopes we haven't modeled (sub-team, environment, etc.).
Why this and not just plugins / vendor marketplaces? Claude Code plugins are real and a good step up over raw git-checked-in CLAUDE.md files. The limitations show up at scale: each plugin is scoped to its publishing repo, so teams duplicate skills across plugins, and you're still locked to a single vendor's client. Full writeup with the technical details: https://www.sleuth.io/post/there-s-an-npm-shaped-hole-in-the...
why this do not belong to git, and does not go with release cycle.
With bigger autonomy, I'd like my skill be tight to my release in prod/commit sha for dev, to figure out what version caused harm/bug. What is the motivation to decouple and make it a separate thing?
Could there be a way to somehow create / export / import a local config of skills? it seems like that could be really useful to share across a single team.
Yes. You can just point sx add at your existing skill directories and it will put them into the git vault which you can easily share via Github access control.
16 comments
[ 3.7 ms ] story [ 24.3 ms ] threadThe short version: sx treats skills, MCP server configs, slash commands, agents, hooks, and rule files as versioned packages. You define them once, push them to a vault (a local folder, a git repo, or our hosted backend), and install them where they belong. There's a lockfile so installs are reproducible, scope levels for org / team / repo / individual, and the CLI translates the same asset into the format each AI client expects.
Supported clients today: Claude Code, Cursor, GitHub Copilot, Cline, Codex, Gemini (CLI / VS Code / JetBrains / Android Studio), Kiro, claude.ai, chatgpt.com. The last two are what let non-engineering teams (marketing, legal, ops) use the same primitive instead of being locked out of the AI-assets ecosystem.
The thing I'd most like feedback on is whether the scope model is the right shape. Org → team → repo → path → individual is what's emerged from talking to ~60 teams over the last six months, but I expect bigger orgs will surface scopes we haven't modeled (sub-team, environment, etc.).
Why this and not just plugins / vendor marketplaces? Claude Code plugins are real and a good step up over raw git-checked-in CLAUDE.md files. The limitations show up at scale: each plugin is scoped to its publishing repo, so teams duplicate skills across plugins, and you're still locked to a single vendor's client. Full writeup with the technical details: https://www.sleuth.io/post/there-s-an-npm-shaped-hole-in-the...
With bigger autonomy, I'd like my skill be tight to my release in prod/commit sha for dev, to figure out what version caused harm/bug. What is the motivation to decouple and make it a separate thing?
I therefore love the idea. Thanks for sharing
I don't disagree there's probably a need and niche, but why not extend and adapt an existing package manager?