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code-review-testing

Anleitung zur Testautorenschaft

Was ist code-review-testing?

Diese Kompetenz (Skill) stellt Leitlinien für das Erstellen von Tests bei Code-Reviews in KI-Agenten-Projekten bereit. Sie priorisiert Integrationstests gegenüber Unit-Tests, insbesondere wenn Änderungen die Kernlogik des Agenten betreffen. Integrationstests befinden sich im Verzeichnis `core/suite` und nutzen `test_codex`, um eine Testinstanz von Codex einzurichten. Bei wesentlichen Logikänderungen oder sichtbaren Verhaltensänderungen des Agenten MUSS ein Integrationstest hinzugefügt und eine Liste dieser Änderungen dokumentiert werden. Unit-Tests sind in eigene `*_tests.rs`-Dateien auszulagern; test-spezifische Funktionen im Hauptcode sind zu vermeiden. Zudem sollen Entwickler prüfen, ob vorhandene Helferfunktionen die Tests lesbarer und effizienter machen. Der Skill ist für Entwickler gedacht, die mit Agentenplattformen wie Claude Code oder Cursor arbeiten und sicherstellen möchten, dass ihre Änderungen robust getestet sind.

Funktioniert mit~Claude Code✓Codex CLI~Cursor

npx skills add https://github.com/openai/codex/tree/main/.codex/skills/code-review-testing

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In Ihrer bevorzugten KI fragen

Öffnet einen neuen Chat, in dem dieser Agent-Skill bereits geladen ist.

ChatGPT Claude Gemini Grok Perplexity DeepSeek

Dokumentation

Für Änderungen am Agenten bevorzuge Integrationstests gegenüber Unit-Tests. Integrationstests befinden sich unter core/suite und verwenden test_codex, um eine Testinstanz von Codex einzurichten.

Funktionen, die die Agentenlogik ändern, MÜSSEN einen Integrationstest hinzufügen:

Gib eine Liste der wichtigsten Logikänderungen und benutzersichtbaren Verhaltensweisen an, die getestet werden müssen.

Falls Unit-Tests erforderlich sind, lege sie in einer dedizierten Testdatei (*_tests.rs) ab. Vermeide test-spezifische Funktionen in der Hauptimplementierung.

Prüfe, ob vorhandene Hilfsfunktionen die Tests lesbarer und schlanker machen.

Individual skills in this repo

This repo contains 19 individual skills — each has its own dedicated page.

babysit-pr

Babysit a GitHub pull request after creation by continuously polling review comments, CI checks/workflow runs, and mergeability state until the PR is merged/closed or user help is required. Diagnose failures, retry likely flaky failures up to 3 times, auto-fix/push branch-related issues when appropriate, and keep watching open PRs so fresh review feedback is surfaced promptly. Use when the user asks Codex to monitor a PR, watch CI, handle review comments, or keep an eye on failures and feedback on an open PR.

code-review

Run a final code review on a pull request

code-review-change-size

Change size guidance (800 lines)

code-review-context

Model visible context

codex-bug

Diagnose GitHub bug reports in openai/codex. Use when given a GitHub issue URL from openai/codex and asked to decide next steps such as verifying against the repo, requesting more info, or explaining why it is not a bug; follow any additional user-provided instructions.

codex-issue-digest

Run a GitHub issue digest for openai/codex by feature-area labels, all areas, and configurable time windows. Use when asked to summarize recent Codex bug reports or enhancement requests, especially for owner-specific labels such as tui, exec, app, or similar areas.

codex-pr-body

Update the title and body of one or more pull requests.

imagegen

Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output should be a bitmap asset rather than repo-native code or vector. Do not use when the task is better handled by editing existing SVG/vector/code-native assets, extending an established icon or logo system, or building the visual directly in HTML/CSS/canvas.

openai/babysit-pr

openai-docs

Use when the user asks how to build with OpenAI products or APIs, asks about Codex itself or choosing Codex surfaces, needs up-to-date official documentation with citations, help choosing the latest model for a use case, or model upgrade and prompt-upgrade guidance; use OpenAI docs MCP tools for non-Codex docs questions, use the Codex manual helper first for broad Codex self-knowledge, and restrict fallback browsing to official OpenAI domains.

openai/test-tui

Guide for testing Codex TUI interactively

path-types

Choose Rust types for operating system paths across the Codex repository. Use when defining new path-bearing types or explicitly migrating existing ones.

plugin-creator

Create and scaffold plugin directories for Codex with a required `.codex-plugin/plugin.json`, optional plugin folders/files, valid manifest defaults, and personal-marketplace entries by default. Use when Codex needs to create a new personal plugin, add optional plugin structure, generate or update marketplace entries for plugin ordering and availability metadata, or update an existing local plugin during development with the CLI-driven cachebuster and reinstall flow.

pushing-ci-changes

Pushing GitHub Actions changes, resolving push rejection, requesting upload exceptions.

remote-tests

Testing against remote executors in integration tests.

skill-creator

Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations.

skill-installer

Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos).

test-tui