by kasperjunge · Agent Tool · ★ 417
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agr The package manager for AI agents. For teams who want to manage agent skills like software packages — the way npm, PyPI, and uv manage code. Install skills from any Git repo into Claude Code, Cursor, Codex, and more, then share them across your team like real dependencies. Why agr agr is for teams who want to manage their agent skills as seriously as they manage their code — the way npm, PyPI, and uv manage software packages. Skills make AI agents better at your work. But today they're copied around by hand, drift between machines, and live in tool-specific folders. agr treats them like real dependencies: declared in one manifest, locked to a version, installed with one command, and identical for every teammate, on every machine, in every tool. That brings the same wins you already get from a package manager for code: Version & pin. records the exact version of every skill, so a skill that works today keeps working tomorrow — no silent upstream changes breaking your agents. Upgrade on purpose, w
| Stars | 417 |
| Forks | 36 |
| Language | Python |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 47.7/100 |
| Open Issues | 9 |
| Last Updated | 2026-03-27 |
| Created | 2026-01-03 |
| Platforms | claude-code, python |
| Est. Tokens | ~136k |
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agent-resources is A package manager for AI agents. Install agent skills from GitHub with a single command.. It is categorized as a Agent Tool with 417 GitHub stars.
agent-resources is primarily written in Python. It covers topics such as agent-skills, claude-code, claude-code-skills.
You can find installation instructions and usage details in the agent-resources GitHub repository at github.com/kasperjunge/agent-resources. The project has 417 stars and 36 forks, indicating an active community.
agent-resources is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to agent-resources on Agent Skills Hub include babysitter, skills, getspecstory. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.