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Official agent skill

Code Change Verification

by openai in openai/openai-agents-python

Run the required final formatting, lint, type, and test checks after eligible SDK changes pass review.

OfficialMITAuto-check passedDevelopment

Install Code Change Verification

skills CLI
$ npx skills add openai/openai-agents-python --skill code-change-verification -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install openai/openai-agents-python code-change-verification --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/openai/openai-agents-python.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/code-change-verification .claude/skills/code-change-verification && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
code-change-verification
GitHub stars
30k
Token cost
~1.4k tokens
SKILL.md length
736 words
Files
4 (incl. scripts)
Skills in repo
14
Repo updated
First seen
Licence
MIT

At a glance

Run the required final formatting, lint, type, and test checks after eligible SDK changes pass review.

  • Works in 8 steps: Keep this skill at… → Codex on macOS/Linux: /usr/bin/env -u… → Other macOS/Linux environments: env… → …
  • Tasks that involve Linting and formatting
  • SKILL.md covers Overview, Quick start, Start condition and host… and Codex execution policy, plus 3 more sections
  • Runs PowerShell and Shell scripts from its folder; calls make and bash; reaches pypi.org; needs OPENAI_API_KEY

What it does

Code Change Verification is an agent skill from openai/openai-agents-python, published by the product's own GitHub organization. Run the required final formatting, lint, type, and test checks after eligible SDK changes pass review.

Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including scripts (for example `agents/openai.yaml` and `scripts/run.sh`).

It sits in Development, covering Linting and formatting. It works with OpenAI, Bash, Linux and macOS. The repository describes itself as: A lightweight, powerful framework for multi-agent workflows. The licence is MIT.

When your agent uses it

  • Tasks that involve Linting and formatting

Example prompts

  • “/code-change-verification”

Requirements

  • Python 3
  • A Bash shell
  • PowerShell
  • A credential in OPENAI_API_KEY

Workflow steps

8 steps, taken from the first numbered list in SKILL.md.

  1. Keep this skill at ./.agents/skills/code-change-verification so it loads automatically for the repository.
  2. Codex on macOS/Linux: /usr/bin/env -u OPENAI_API_KEY OPENAI_AGENTS_TEST_IN_CODEX_SANDBOX=1 UV_DEFAULT_INDEX=https://pypi.org/simple bash…
  3. Other macOS/Linux environments: env UV_DEFAULT_INDEX=https://pypi.org/simple bash .agents/skills/code-change-verification/scripts/run.sh.
  4. Windows: powershell -ExecutionPolicy Bypass -File .agents/skills/code-change-verification/scripts/run.ps1.
  5. On macOS/Linux, the script runs make format, make lint, make typecheck, and make tests sequentially and stops at the first failure…
  6. The Bash script streams each command's output directly. The Windows wrapper retains parallel lint, typecheck, and test steps with periodic…
  7. If any command fails, fix the issue, rerun the script, and report the failing output.
  8. Confirm completion only when all commands succeed with no remaining issues.

What it can do on your machine

Read from SKILL.md and the folder at commit 71c2da4. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 2 files in scripts/ (PowerShell and Shell), which the agent can run.

    Shell commands in SKILL.md call:

    • make
    • bash

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • pypi.org

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • OPENAI_API_KEY

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Code Change Verification loads about 1.4k tokens when it runs. Until then it costs about 32 tokens; SKILL.md has 736 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~32
When it runs · the whole SKILL.md, loaded when a task matches
~1.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from openai/openai-agents-python at commit 71c2da4, republished under its MIT licence (© openai). 736 words, ~1,375 tokens.

Download SKILL.mdSave it as .claude/skills/code-change-verification/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
code-change-verification
description
Run the required final formatting, lint, type, and test checks after eligible SDK changes pass review.

Code Change Verification

Overview

Ensure work is only marked complete after formatting, linting, type checking, and tests pass. Use this skill when changes affect runtime code, tests, or build/test configuration. You can skip it for docs-only or repository metadata unless a user asks for the full stack. This is a post-review final gate: when $implementation-final-review applies, do not invoke the broad stack until its clean-review condition applies to the stable task diff.

Quick start

  1. Keep this skill at ./.agents/skills/code-change-verification so it loads automatically for the repository.
  2. Codex on macOS/Linux: /usr/bin/env -u OPENAI_API_KEY OPENAI_AGENTS_TEST_IN_CODEX_SANDBOX=1 UV_DEFAULT_INDEX=https://pypi.org/simple bash .agents/skills/code-change-verification/scripts/run.sh.
  3. Other macOS/Linux environments: env UV_DEFAULT_INDEX=https://pypi.org/simple bash .agents/skills/code-change-verification/scripts/run.sh.
  4. Windows: powershell -ExecutionPolicy Bypass -File .agents/skills/code-change-verification/scripts/run.ps1.
  5. On macOS/Linux, the script runs make format, make lint, make typecheck, and make tests sequentially and stops at the first failure. Parallelism inside each Make target, including pytest workers, is unchanged.
  6. The Bash script streams each command's output directly. The Windows wrapper retains parallel lint, typecheck, and test steps with periodic heartbeat updates.
  7. If any command fails, fix the issue, rerun the script, and report the failing output.
  8. Confirm completion only when all commands succeed with no remaining issues.

Start condition and host capacity

  • During iterative review, use only focused tests and a narrowly targeted static check when the changed typing boundary requires one. Defer repository-wide make typecheck and the rest of this complete stack until review is clean.
  • Immediately before starting the complete stack, use available read-only task or process evidence to check whether another repository-wide test, typecheck, build, examples runner, or integration command is already active on the same host.
  • When concrete contention is visible, continue useful non-heavy work such as review, remediation, evidence preparation, or focused checks, then check again later. Do not create or wait on a repository lock, host-wide mutex, or sentinel file.
  • Start automatically once review is clean, the diff is stable, and observable host capacity is available. Do not require a user-triggered finalize message. If host telemetry is unavailable, do not block solely because capacity cannot be measured.

Codex execution policy

Repository verification and all child processes must remain in the normal Codex workspace sandbox. Never request elevated sandbox permissions for the verification wrapper, and never retry the wrapper with broader host access after a failure.

On macOS, tests marked requires_native_macos_sandbox need to start their own sandbox-exec process. The Codex command sets OPENAI_AGENTS_TEST_IN_CODEX_SANDBOX=1, which skips only that marker before nested sandbox creation. All other tests remain enabled. Ordinary local and CI runs do not set this variable and therefore keep the marked tests enabled.

The marked tests run separately on a disposable GitHub-hosted macOS runner. If that trusted runner is unavailable, report the missing native-macOS coverage; do not compensate by weakening the Codex sandbox boundary.

Show full SKILL.md (277 more words)Show less

Environment setup

The verification scripts assume repository dependencies are already installed. Do not run make sync as part of every verification pass; use it for a fresh checkout, after dependency files change, or when dependency resolution fails before the checks start.

On Linux, some Python packages with native extensions may require system packages such as libffi-dev, Python development headers, or build tools. If verification cannot start because one of these packages is missing, treat it as a local environment setup issue. Install the missing dependency when possible, or report the failing command and missing dependency in the PR test plan before rerunning verification in a prepared environment.

Manual workflow

  • For a fresh checkout, or if dependencies are not installed or have changed, run make sync first to install dev requirements via uv.
  • Run from the repository root with make format first, then make lint, make typecheck, and make tests.
  • Do not skip steps; stop and fix issues immediately when a command fails.
  • Run the manual steps sequentially and stop at the first failure. Keep the parallelism provided by each Make target.
  • Re-run the full stack after applying fixes so the commands execute in the required order.

Resources

scripts/run.sh
  • Runs make format, make lint, make typecheck, and make tests sequentially from the repository root. It streams output, preserves the first failure or cancellation status, and cleans up the active step's process group before continuing or exiting.
scripts/run.ps1
  • Windows-friendly wrapper that runs the same sequence with make format first and the remaining steps in parallel with fail-fast semantics, plus periodic heartbeat updates while work is still running. Use from PowerShell with execution policy bypass if required by your environment.

© openai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (scripts) in .agents/skills/code-change-verification of openai/openai-agents-python.

  • SKILL.md
  • agents/openai.yaml
  • scripts/run.ps1
  • scripts/run.sh

Open the folder on GitHubat commit 71c2da4

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Debug CIweb-infra-dev/rslint460—~2.8kAutomated safety check: PassMIT
Cm Checkkingxiaozhe/cm-workflow104—~1.3kAutomated safety check: PassMIT
Oh My PoshJanDeDobbeleer/oh-my-posh24k—~319Automated safety check: PassMIT

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Works with

Categories

Questions about Code Change Verification

What does Code Change Verification do?

Run the required final formatting, lint, type, and test checks after eligible SDK changes pass review. Code Change Verification is an agent skill from openai/openai-agents-python, published by the product's own GitHub organization. Run the required final formatting, lint, type, and test checks after eligible SDK changes pass review.

When should I use Code Change Verification?

Code Change Verification fits situations like: tasks that involve Linting and formatting.

How do I install Code Change Verification in Claude Code?

Run `npx skills add openai/openai-agents-python --skill code-change-verification -a claude-code`. Or copy the skill folder (.agents/skills/code-change-verification in openai/openai-agents-python) into .claude/skills/code-change-verification in your project. Claude Code loads it when a task matches its description.

How do I install Code Change Verification in Codex?

Run `npx skills add openai/openai-agents-python --skill code-change-verification -a codex`. Or copy the skill folder (.agents/skills/code-change-verification in openai/openai-agents-python) into .agents/skills/code-change-verification in your project. Codex loads it when a task matches its description.

Can I use Code Change Verification in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add openai/openai-agents-python --skill code-change-verification -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/code-change-verification, .gemini/skills/code-change-verification, .github/skills/code-change-verification and .opencode/skills/code-change-verification in your project.

What does Code Change Verification need to run?

Going by SKILL.md and its folder, Code Change Verification needs PowerShell and a shell for the scripts in its folder, the command-line tools its instructions call (make and bash) and credentials named OPENAI_API_KEY. Our summary lists: Python 3; A Bash shell; PowerShell; A credential in OPENAI_API_KEY.

Does Code Change Verification access the network?

SKILL.md names 1 domain. In commands or code: pypi.org; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Code Change Verification safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Code Change Verification use?

Code Change Verification is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Code Change Verification use?

About 1.4k tokens (SKILL.md is roughly 5.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Code Change Verification?

Skills that share tags, products or a category with Code Change Verification: Gridbash Panes (jasonsuhari/gridbash, 134 stars), AdvPL UTF-8 to CP1252 Converter (totvs/engpro-advpl-tlpp-skills, 141 stars), Debug CI (web-infra-dev/rslint, 460 stars) and Cm Check (kingxiaozhe/cm-workflow, 104 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Code Change Verification?

openai (a GitHub organization, an official publisher) maintains it in openai/openai-agents-python, which has 29,873 GitHub stars. The repository holds 14 skills in this directory. The repository was last updated on October 7, 2026.

Source: openai/openai-agents-python on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.