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openai/codex-action — Running Codex CLI in GitHub Actions

Official action repository that runs Codex CLI in GitHub Actions workflows, manages the permission scope, and posts the final-message to PR comments.

Repositoryopenai/codex-action ↗

Official action repository that runs Codex CLI in GitHub Actions workflows, manages the permission scope, and posts the final-message to PR comments.

stars
★ 1.3K
Forks
181
Language
JavaScript
License
Apache-2.0
Read original source ↗View on GitHub ↗

openai/codex-action is the official action repository for running Codex CLI in GitHub Actions workflows. Codex CLI is a command-line tool that performs coding work in the terminal, and this action carries out that work inside event-driven workflows, then passes the execution result to the next step. The repository was created on October 1, 2025 (UTC), and no public release version is given.

The core design of this action is the strict management of the permissions granted to Codex, that is, the range of tasks Codex is allowed to perform. The README explains that it installs Codex CLI while configuring a secure proxy for the Responses API (an intermediary layer that mediates API requests). It addresses the permission scope and the API call path together, and the example workflow in the README reviews the PR changes and then posts Codex's final-message (final summary message) as a PR comment. The implementation language is JavaScript, the license is Apache-2.0, and the repository has 1275 stars.

However, the provided record contains no performance measurements or real adoption cases. Because there is no release version, it is hard to track the change history on a per-version basis, and the repository description field is also empty. The score record likewise has only the momentum score of 3.0 (out of 10) filled in, while the novelty, technical, and quality scores are blank. These numbers alone make it difficult to read off the repository's actual range of use and maintenance cadence. All that can be confirmed right now is the example workflow contained in the README, and judgments about stability and maintenance cadence are better made once more records have piled up.