[2608.10906] GitSkills: A Dataset of Agent Skills on GitHub

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arXiv:2608.10906 (cs)

[Submitted on 11 Aug 2026]

Title:GitSkills: A Dataset of Agent Skills on GitHub

Authors:Giuseppe Destefanis, Daniel Graziotin, Matteo Vaccargiu, Marco Ortu<br>View a PDF of the paper titled GitSkills: A Dataset of Agent Skills on GitHub, by Giuseppe Destefanis and 3 other authors

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Abstract:An agent skill is a folder containing a this http URL file with instructions for a language-model agent, optionally accompanied by scripts and reference files. The agent loads the skill when it judges that a task matches the skill description. Anthropic introduced the format in October 2025 as an open specification. Nine months later, we find that skill files in the millions sit in public GitHub repositories. Skills are unlike the artifacts the SE research community usually mines: they are written mainly in natural language, a model selects them probabilistically at run time, and no compiler or type checker verifies the selection. They also have no central registry or package manager, so they spread by copying folders between repositories. How developers write, reuse, and maintain skills is therefore an empirical question, and no existing dataset records this population. We present GitSkills, a dataset of 3,797,117 this http URL files collected from 282,200 public repositories in July 2026. The dataset retains every file occurrence with its repository, path, and content hash. It groups identical files into 1,877,981 distinct contents and enriches one representative per group with the full text, parsed front matter, folder contents, repository metadata, and, for a subset, the commit history of the file. A single self- contained SQLite file supports research on the adoption, reuse, structure, authorship, maintenance, and security of agent skills.

Comments:<br>Giuseppe Destefanis, Daniel Graziotin, Matteo Vaccargiu, and Marco Ortu. 2027. GitSkills: A Dataset of Agent Skills on GitHub. In Proceedings of the 24th International Conference on Mining Software Repositories (MSR '27). Association for Computing Machinery, New York, NY, USA, 3 pages. To appear

Subjects:

Software Engineering (cs.SE); Artificial Intelligence (cs.AI)

Cite as:<br>arXiv:2608.10906 [cs.SE]

(or<br>arXiv:2608.10906v1 [cs.SE] for this version)

https://doi.org/10.48550/arXiv.2608.10906

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arXiv-issued DOI via DataCite

Submission history<br>From: Daniel Graziotin [view email]<br>[v1]<br>Tue, 11 Aug 2026 13:28:27 UTC (8 KB)

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