What still feels missing is the middle layer: how teams and organizations share AI agent skills, track provenance, and keep them safe to use.
Agent Skill Harbor is an OSS skill management platform for that layer. It is GitHub-native, DB-less, and serverless by design, because skills are mostly text artifacts that already fit naturally in Git.
It collects skills from GitHub repos, tracks provenance, supports governance and safety checks, and publishes a static catalog site with GitHub Actions and GitHub Pages.
Repo: https://github.com/skill-mill/agent-skill-harbor Demo: https://skill-mill.github.io/agent-skill-harbor-demo/
CharlieDigital•1h ago
Codex, for example, currently does not support this[0].
Then we can just point to an MCP server and have the MCP server dynamically compose the set of skills without needing to do any syncs, git sub-modules, etc.
[0] https://github.com/openai/codex/issues/5059
stingraycharles•1h ago
CharlieDigital•58m ago
Don't overthink it; it's all just text. I want to serve the text from HTTP instead of having to deploy via `git` and sync. I want to be able to dynamically generate that text on the server based on the identity of the user, their role, what team they're in, what repo they're working on.
I don't want static skills. That users have to remember to sync and keep up to date.
climike•1h ago
hatappo•1h ago
Packaging skills with libraries/CLIs and letting agents discover them from installed packages makes a lot of sense. I see Harbor as addressing a different layer on top of that: organizational collection, cataloging, provenance, governance, and safety.
hatappo•1h ago