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Agent Skill · 开发

codex(Codex 编程助手)

codex 用于补充开发相关能力,适合在 OpenClaw 中需要让 Agent 承接开发相关任务时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

codex 是开发类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为调用外部服务;许可证为 MIT-0,第三方扫描已通过,按安装量在开发类的 21,746 个 Skill 里排第 1,384。

总安装 31,041周安装 1,268GitHub Stars 1下载 9,941核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.0

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:codex(Codex 编程助手)
来源仓库:https://github.com/ivangdavila/codex
安装命令:
openclaw skills install codex
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install codex

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

通过显式批准、沙箱选择、MCP 边界和 PR 就绪验证工作流程,安全地使用 Codex 进行存储库感知编码。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install codex;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要调用外部服务,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

codex 怎么安装?

在终端执行 openclaw skills install codex。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

codex 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

codex 需要什么权限?

权限级别是调用外部服务。该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

codex 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

codex 用的人多吗?

公开数据是累计安装 31,041 次,近一周安装 1,268 次,下载 9,941 次,GitHub 1 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

codex 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理开发类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
codex

Codex 编程助手 · 本页

31,0411调用外部服务MIT-0通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
Codex
slug
codex
version
1.0.0
homepage
https://clawic.com/skills/codex
description
Use Codex safely for repo-aware coding with explicit approvals, sandbox choices, MCP boundaries, and PR-ready verification workflows.
changelog
Initial release with repo-safe execution, approval and sandbox guidance, MCP and cloud guardrails, and review-ready handoff workflows.
metadata
{"clawdbot":{"emoji":"🧭","requires":{"bins":["codex"],"bins.optional":["git","rg"],"env.optional":["OPENAI_API_KEY"],"config":["~/codex/","~/.codex/config.toml"]},"os":["linux","darwin","win32"],"configPaths":["~/codex/","~/.codex/config.toml"]}}

When to Use

User wants to use Codex as a real coding agent instead of a generic chat assistant: inspect a repo, make bounded edits, run review mode, resume work, use MCP safely, or hand work off with clear verification evidence.

Use this skill when the hard part is not "write code" but "make Codex behave safely and predictably" across CLI, exec, review, resume, MCP, app-server, cloud tasks, or local OSS-provider workflows.

Architecture

Memory lives in ~/codex/. If ~/codex/ does not exist, run setup.md. See memory-template.md for structure.

~/codex/
|-- memory.md          # Durable activation boundaries and operating defaults
|-- repo-profiles.md   # Per-repo conventions, test surface, and blast-radius notes
|-- safety.md          # Sandbox, approval, and trust defaults
|-- mcp-notes.md       # Approved MCP servers, scopes, and rejection reasons
`-- incidents.md       # Stuck sessions, failed commands, and recovery patterns

Quick Reference

Load only the smallest file needed for the current blocker.

TopicFile
Setup guidesetup.md
Memory templatememory-template.md
Install, login, and first-run checksinstall-and-auth.md
Repo execution and codex exec workflowsrepo-execution.md
Approval modes and sandbox choicesapprovals-and-sandbox.md
MCP, app-server, cloud, and local-provider guardrailsmcp-and-cloud.md
Review mode and handoff patternsreview-and-handoffs.md
Recovery playbooks for auth, stuck sessions, and wrong-scope worktroubleshooting.md

Requirements

  • codex binary installed and working on the target machine.
  • Active authentication through codex login or an explicit OPENAI_API_KEY flow when that mode is chosen.
  • git available when the task involves repository inspection, diff review, or commit-ready workflows.
  • Explicit user approval before dangerous sandbox bypass, remote MCP usage, Codex Cloud apply, production commands, or any operation with irreversible side effects.
  • Treat model names, features, and app-server behavior as live product surface: verify with codex --help, subcommand help, or official docs instead of hardcoding stale assumptions.

Operating Coverage

This skill treats Codex as an operational coding surface, not as generic AI advice. It covers:

  • interactive Codex CLI usage with explicit working-directory and safety choices
  • non-interactive codex exec and codex review workflows
  • resume, fork, and handoff-friendly session recovery
  • sandbox and approval policy selection by blast radius
  • MCP server trust decisions and local-versus-remote tool boundaries
  • Codex app-server and cloud task usage only when their extra trust and review requirements are explicit
  • local OSS-provider routing via --oss and --local-provider when the user intentionally wants local execution

Data Storage

Keep only durable Codex operating context in ~/codex/:

  • which repos or workspaces are approved for Codex use
  • default sandbox and approval posture per task type
  • preferred execution surfaces: interactive CLI, exec, review, cloud, or local OSS provider
  • approved MCP servers and what each one is allowed to touch
  • recurring recovery notes for wrong directory, dirty worktree, stalled commands, or broken auth

Core Rules

1. Preflight the Task Before Codex Acts

  • Lock five facts first: target repo, current directory, dirty worktree state, required permissions, and expected verification.
  • If any of those are unclear, pause and resolve them before running Codex with write capability.
  • "Start coding" is never the first step in an unfamiliar repo.

2. Choose the Operating Mode Explicitly

  • Use interactive Codex for exploratory repo work, codex exec for bounded non-interactive execution, and codex review for review-first tasks.
  • If resuming or branching prior work, prefer resume or fork over re-describing the entire context from scratch.
  • Treat cloud, app-server, and MCP-assisted runs as separate modes with separate risk.

3. Match Sandbox and Approval to Blast Radius

  • Read-only fits inspection, planning, and low-trust exploration.
  • Workspace-write fits normal local coding in the approved repo.
  • Full access or dangerous bypass is a special-case mode that needs explicit user intent and an external sandbox story.
  • Do not normalize high-trust modes for convenience.

4. Read the Repo Before Editing It

  • Inspect tree shape, git status, entrypoints, conventions, and test surface before proposing edits.
  • When the worktree is already dirty, separate user changes from agent changes and avoid destructive cleanup.
  • Codex should adapt to the repo, not force the repo into a generic workflow.

5. Keep Changes Reviewable and Scoped

  • Favor minimal diffs, targeted commands, and explicit file ownership.
  • Avoid unrelated cleanup, speculative refactors, or "while here" edits unless requested.
  • If a command or edit expands scope, stop and surface that expansion immediately.

6. Treat Auth, MCP, and Cloud as Trust Boundaries

  • A tool being available does not mean it is approved.
  • Review each MCP server for scope, data access, and side effects before enabling it.
  • Use existing login sessions when possible; never scrape secrets from local files without clear user intent.
  • Inspect cloud diffs before applying them locally.

7. Verify Outcomes and Leave a Handoff Trail

  • A successful Codex run ends with checks, not with code edits alone.
  • Report what changed, what was verified, what failed, and what remains risky.
  • For interrupted or long-running work, leave a crisp checkpoint that another operator can resume without guesswork.

Codex Traps

  • Running Codex in the wrong directory -> edits land in the wrong repo or outside intended scope.
  • Treating workspace-write as harmless -> it still writes real files and can widen a diff quickly.
  • Using --dangerously-bypass-approvals-and-sandbox for routine work -> convenience becomes unreviewable risk.
  • Enabling MCP servers because they are available -> hidden data reach and side effects expand silently.
  • Applying cloud output without reviewing the diff -> local repo changes become opaque.
  • Letting Codex work through a dirty tree without clarifying ownership -> review noise and accidental overwrite risk.
  • Re-running vague prompts after interruption -> duplicated work and inconsistent verification.

External Endpoints

Only these external categories are allowed unless the user explicitly approves more:

EndpointData SentPurpose
https://api.openai.comprompts, selected repository context, tool results, and execution metadata needed for Codex runsCodex model execution, cloud tasks, login-linked agent work
https://developers.openai.com/*doc queries onlyVerify current Codex product behavior and configuration details
https://{user-approved-mcp-host}request payloads required by the specific MCP serverOptional user-approved tool access beyond the local machine

No other data is sent externally unless the user explicitly approves additional MCP servers, Git remotes, or service endpoints.

Security & Privacy

Data that leaves your machine:

  • prompts and the repo context selected for Codex runs against OpenAI services
  • optional MCP payloads only for user-approved MCP servers
  • optional cloud task payloads and diffs when Codex Cloud is intentionally used

Data that stays local:

  • ~/.codex/config.toml and the user's local Codex session/config state
  • durable operating notes under ~/codex/
  • local diffs, verification output, and repo metadata unless the user explicitly pushes or uploads them

This skill does NOT:

  • assume dangerous bypass is acceptable by default
  • enable remote MCP or cloud apply silently
  • scrape tokens from arbitrary files to "help" auth succeed
  • hide sandbox or approval choices from the user
  • claim that CLI, app-server, cloud, and local --oss flows have identical risk

Trust

By using this skill, Codex work may send prompts and selected repository context to OpenAI, plus any optional user-approved MCP endpoints. Only install if you trust those services with that data.

Scope

This skill ONLY:

  • helps operate Codex safely and effectively in real coding environments
  • structures repo work into explicit execution, review, and handoff modes
  • keeps durable memory for approved repos, safety posture, and recurring recovery patterns

This skill NEVER:

  • treat every available Codex feature as automatically approved
  • recommend destructive git cleanup as a default fix
  • blur the line between local-only, cloud, and MCP-assisted execution
  • modify its own skill files

Related Skills

Install with clawhub install <slug> if user confirms:

  • agentic-engineering - Strengthen the human workflow around parallel coding agents and blast-radius thinking.
  • coding - Improve implementation quality once Codex is operating inside the right repo boundaries.
  • git - Handle branches, diffs, and non-destructive repository recovery safely.
  • api - Reuse structured API and request-debugging patterns when Codex integrates with services.
  • workflow - Turn recurring Codex tasks into repeatable, reviewable execution paths.

Feedback

  • If useful: clawhub star codex
  • Stay updated: clawhub sync

平台分布

OpenClaw

75.68%
按下载量换算7,523

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

调用外部服务

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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