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AgentLogs: A Dataset for Opening the Black Box of GitHub's Cloud Agent — arXiv:2608.29204

Source: arXiv (en)
Original: https://arxiv.org/abs/2608.29204
License (as archived): CC0-1.0
Archived: 2026-10-17T07:47:34.174Z
SHA-256 of the archived text: 1143120a86149294891b1136c220b162f1537adb7e9bc90ef117a7b5f04dbafe
Stable URL of this page: https://metraipolis.com/documento/dc_a4e48e423abb

How to cite

AgentLogs: A Dataset for Opening the Black Box of GitHub's Cloud Agent — arXiv:2608.29204 — arXiv (en), https://arxiv.org/abs/2608.29204 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_a4e48e423abb (Metraipolis archive dc_a4e48e423abb, sha256 1143120a86149294891b1136c220b162f1537adb7e9bc90ef117a7b5f04dbafe)

BibTeX

@misc{dca4e48e423abb,
  title = {AgentLogs: A Dataset for Opening the Black Box of GitHub's Cloud Agent — arXiv:2608.29204},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2608.29204},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_a4e48e423abb; sha256 1143120a86149294891b1136c220b162f1537adb7e9bc90ef117a7b5f04dbafe},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2608.29204. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Generative AI-based software engineering agents are becoming routine contributors to real-world software projects. On GitHub, developers can assign tasks to the Copilot cloud agent, which autonomously explores the repository, edits code, runs commands, and opens or reviews pull requests, producing a detailed log of every step along the way. While existing datasets capture outcomes of agent contributions, such as agent-authored pull requests, the process by which agents produce these contributions remains largely unexplored. To address this gap, we introduce AgentLogs, a large-scale dataset of agent activity on GitHub. AgentLogs comprises 307,416 agent tasks and 549,239 agent sessions in 35,810 of the 1,812,362 popular public repositories that we scanned, together with 64,255,174 session log entries that record each agent run step by step, including prompts, intermediate reasoning, tool calls (e.g., file edits, git operations, and GitHub interactions), and token usage. By exposing not only what agents contribute but also how they work, AgentLogs enables research on agent behavior, efficiency and cost, task formulation, failure modes, and human-agent collaboration in agentic software engineering.

Tema degli esploratori: agenti e intelligenza artificiale (retro-catalogo arXiv: annunci del 2026-09-01 in cs.AI).
Categorie arXiv: Software Engineering (cs.SE) ; Artificial Intelligence (cs.AI).
Pagina del lavoro: https://arxiv.org/abs/2608.29204 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-17T07:28:26.730Z dalla pagina https://arxiv.org/catchup/cs.AI/2026-09-01?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).