Code Change Verification

Code Change Verification is an individual skill from OpenAI’s official open-source openai-agents-python repository. Its direct primary source is https://github.com/openai/openai-agents-python/tree/main/.agents/skills/code-change-verification. The skill describes a final verification workflow for changes that affect runtime code, tests, or build and test configuration. Rather than judging a change from a local snapshot alone, the workflow guides the user through formatting, linting, type checking, and tests. This creates an auditable technical gate before work is declared complete.

Purpose and audience

According to the provider, the skill should be used as a complete final gate only after a clean implementation review. During development, focused tests and narrowly targeted static checks are more useful because they provide fast feedback. The broad stack belongs at the end of a stable change. The skill fits teams that want to protect Python SDK changes reproducibly and need a clear statement about whether the expected quality checks passed. It does not replace product acceptance, security analysis, or a review of whether the change actually solves the right requirement.

The intended sequence

The official instructions provide a script for macOS and Linux that runs from the repository root. In the normal order it invokes make format, make lint, make typecheck, and make tests, stopping at the first failure. Formatting may modify files, while linting, type checking, and tests expose problems. For Codex in a sandbox, the source names an environment that removes the OpenAI key from the process and enables the intended sandbox test mode. Other local environments should run the script with their appropriate non-privileged environment. Windows uses the supplied PowerShell wrapper.

Failure handling and evidence

When a command fails, the issue should be fixed and the complete workflow rerun. A previously successful partial step does not prove that later checks will pass. The workflow streams output so a reviewer can inspect the concrete cause. Before starting the complete stack, the source recommends checking for other repository-wide tests, type checks, builds, examples runners, or integration commands already active on the host. Visible contention is a reason to continue review or preparation and check again later, not to introduce a repository lock, host-wide mutex, or sentinel file.

Security and boundaries

The skill does not authorize elevated permissions. It should run inside the normal workspace sandbox and must not be retried with broader host access after a failure. Tests can still depend on local packages, platform behavior, or missing system dependencies. According to the provider, specially marked native macOS sandbox tests may run on a trusted GitHub-hosted runner; when that runner is unavailable, the missing coverage must be reported openly. No verification stack proves complete security. Do not store API keys, tokens, personal data, or confidential test content in verification logs or example files. Local tests also do not mean that connected model calls are processed locally.

Practical interpretation

The value of this skill is its explicit end-to-end gate: a change is complete only after all required stages pass and no remaining issues are present. For an unstable change, the full run can be premature; focused tests are the better intermediate step. This description was checked against the official skill file and official OpenAI Agents documentation on September 9, 2026. The repository is open source and licensed under Apache-2.0 according to the provider. Always verify current scripts, dependencies, and platform notes in the primary source.