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Agent Skill · 开发

openclaw-openai-multi-account(OpenClaw OpenAI multi account 安全)

openclaw-openai-multi-account 用于辅助安全审计、权限检查和凭据风险排查,适合在 OpenClaw 中需要复核安全边界、认证流程或敏感配置时使用。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。

openclaw-openai-multi-account 是开发类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为接触敏感数据;许可证为 MIT-0,第三方扫描有提醒项,按安装量在开发类的 21,746 个 Skill 里排第 3,175。

总安装 12,432周安装 518GitHub Stars 公开资料未说明下载 4,144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
1.0.2

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:openclaw-openai-multi-account(OpenClaw OpenAI multi account 安全)
来源仓库:https://github.com/tutouguai1933/openclaw-openai-multi-account
安装命令:
openclaw skills install openclaw-openai-multi-account
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 openclaw-openai-multi-account

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。

OpenClaw openai multi account 管理多个 OpenAI OAuth 登录账户,支持快照切换。提供真实活跃账户检测与 5 小时缓存机制优化体验。适用于多账号轮换使用以规避速率限制或测试不同身份。通过 clawhub 安装后导入 OAuth token 列表即可管理。

务必妥善保管各账户凭据防止泄露或被盗用。

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 openclaw-openai-multi-account;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

    它需要接触敏感数据,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

openclaw-openai-multi-account 怎么安装?

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

openclaw-openai-multi-account 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。

openclaw-openai-multi-account 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

openclaw-openai-multi-account 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。

openclaw-openai-multi-account 用的人多吗?

公开数据是累计安装 12,432 次,近一周安装 518 次,下载 4,144 次。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。

openclaw-openai-multi-account 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

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。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 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。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 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
openclaw-openai-multi-account

OpenClaw OpenAI multi account 安全 · 本页

12,432—接触敏感数据MIT-0有提醒

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
openclaw-openai-multi-account
description
Manage multiple OpenAI OAuth login accounts inside OpenClaw, including OpenAI Codex OAuth account snapshots, switching, real active-account detection, 5-hour and weekly quota inspection via Codex CLI cache, ACTIVE metadata repair, auto-enrollment of newly logged-in accounts, same-model auto-rotation near exhaustion, and fallback to a backup model such as Bailian when all OpenAI accounts are unavailable. Use when the user asks about multiple OpenAI OAuth accounts in OpenClaw, OpenAI/Codex account switching, the current real active account, local saved accounts, 5h or weekly remaining quota, OAuth re-login, automatic account rotation, or fallback behavior in OpenClaw.

OpenClaw OpenAI Account Switcher

Use this skill for multiple OpenAI OAuth login accounts managed inside OpenClaw, especially OpenClaw's own openai-codex OAuth accounts, not just plain Codex CLI account files.

What this skill does

  • Save the current OpenClaw openai-codex:default OAuth profile as a named snapshot
  • Add a new account by running openclaw models auth login --provider openai-codex
  • Switch all agents to a named snapshot
  • Show the current active account (email/account id when available)
  • Show cached/observed 5-hour and weekly usage when quota data can be collected
  • Auto-switch to the account with remaining quota
  • Fall back to a backup model when all accounts are exhausted

Files

  • Main script: scripts/openclaw-openai-accounts.py
  • Regression test script: scripts/test_openclaw_openai_accounts.py
  • State store: ~/.openclaw/openai-codex-accounts/

Run the bundled regression suite with:

python3 scripts/test_openclaw_openai_accounts.py

Daily local check command:

/home/djy/.openclaw/workspace-taizi/bin/check-openai-multi-account

It writes timestamped logs under:

  • /home/djy/.openclaw/workspace-taizi/data/openai-multi-account-checks/

First use

List current snapshots:

python3 scripts/openclaw-openai-accounts.py list
list, add, use, auto, and cron-check all reconcile the current live OpenClaw login back into the saved account list before reporting or switching, so out-of-band openclaw models auth login --provider openai-codex changes are picked up automatically. The same reconciliation also keeps related OpenClaw auth metadata in sync: - add missing auth.profiles email aliases in openclaw.json - keep auth.order.openai-codex aligned with the saved account list and current active account - add/remove matching named email profiles in each agent auth-profiles.json - prune stale aliases that no longer correspond to any saved account

Probe real quota via Codex CLI and show it in the list:

python3 scripts/openclaw-openai-accounts.py list --verbose --probe

Add an account (interactive OAuth login):

python3 scripts/openclaw-openai-accounts.py add --name work

Switch account:

python3 scripts/openclaw-openai-accounts.py use work

Auto-pick best account or fall back:

python3 scripts/openclaw-openai-accounts.py auto

Auto-check mode for cron/systemd (single-line notification-friendly output):

python3 scripts/openclaw-openai-accounts.py cron-check

Important behavior

1. Canonical auth source

This skill treats OpenClaw agent auth files as the source of truth:

  • ~/.openclaw/agents/<agent>/agent/auth-profiles.json

It updates all configured agents to keep openai-codex:default aligned.

2. Quota collection

Quota collection works in two modes:

  • Preferred: if a matching Codex CLI account snapshot exists and codex is installed, collect real 5-hour / weekly rate-limit data
  • Fallback: if no Codex CLI snapshot exists, keep local observations and report that quota is unknown

3. Fallback model

Default backup model is:

  • bailian/qwen3.5-plus

You can also override defaults via environment variables:

  • OPENCLAW_HOME — OpenClaw data root (default ~/.openclaw)
  • OPENCLAW_PRIMARY_AGENT — canonical agent whose auth file is treated as the real active auth (default taizi)
  • OPENCLAW_FALLBACK_MODEL — backup model to use when all OpenAI accounts are exhausted (default bailian/qwen3.5-plus)

Override it with:

python3 scripts/openclaw-openai-accounts.py auto --fallback-model bailian/glm-5

4. Automatic checks

Run periodically with cron/systemd/loop. Example one-shot command:

python3 scripts/openclaw-openai-accounts.py auto --json

A good interval is every 10-15 minutes.

For unattended auto-switching, prefer a two-stage threshold with a short inactivity guard. The bundled script now supports:

python3 scripts/openclaw-openai-accounts.py auto --five-hour-switch-at 80 --five-hour-hard-switch-at 90 --weekly-switch-at 90 --weekly-hard-switch-at 95 --inactive-minutes 3
python3 scripts/openclaw-openai-accounts.py cron-check --five-hour-switch-at 80 --five-hour-hard-switch-at 90 --weekly-switch-at 90 --weekly-hard-switch-at 95 --inactive-minutes 3

This means:

  • when 5-hour usage reaches 80% (about 20% left), attempt switching only if no non-cron session across configured agents has been active within the last 3 minutes
  • when 5-hour usage reaches 90% (about 10% left), switch immediately to avoid hitting rate limits, even if sessions are active
  • when weekly usage reaches 90% (about 10% left for the week), attempt switching only if no non-cron session across configured agents has been active within the last 3 minutes
  • when weekly usage reaches 95% (about 5% left for the week), switch immediately to preserve the remaining weekly quota

Recommended policy

Use this policy by default:

  • Check every 10 minutes
  • At 5-hour usage 80%: try switching only when all non-cron sessions have been inactive for 3 minutes
  • At 5-hour usage 90%: switch immediately to avoid rate limits
  • At weekly usage 90%: try switching only when all non-cron sessions have been inactive for 3 minutes
  • At weekly usage 95%: switch immediately to preserve the remaining weekly quota
  • Prefer staying on the current account if it is still under both soft thresholds
  • Prefer same-model account rotation (openai-codex/gpt-5.4 → another openai-codex/gpt-5.4 account)
  • Fall back to a backup model only when all accounts are above threshold or quota is unknown

Default thresholds in the script:

  • 5-hour soft switch threshold: 80%
  • 5-hour hard switch threshold: 90%
  • weekly soft switch threshold: 90%
  • weekly hard switch threshold: 95%
  • inactivity guard: 3 minutes

Recommended workflow

  1. Add at least two accounts
  2. Run list --verbose to verify identities
  3. Run auto to validate selection logic
  4. When the user wants automation, schedule auto periodically
  5. When switching happens, report:

- active account name - email - 5-hour usage - weekly usage - current primary model / fallback model

Health states

The script now distinguishes these states:

  • healthy: token works and rate limits were read successfully
  • auth-invalid: token/refresh/login is invalid and the account should be re-logged-in
  • plan-unavailable: token exists but the workspace/plan/model is not usable
  • quota-unknown: quota could not be determined yet

These states appear in list --verbose and status.

Important implementation note

After inspecting OpenClaw source (/tmp/openclaw/src/commands/models/auth.ts and /tmp/openclaw/src/commands/onboard-auth.credentials.ts) plus live runtime files, the built-in openclaw models auth login --provider openai-codex has these practical semantics:

  1. the live credential is used via openai-codex:default
  2. switching accounts writes the new token into openai-codex:default
  3. email-specific profiles such as openai-codex:user@example.com are kept as named records
  4. sibling agent auth stores are synced together
  5. existing usageStats and lastGood are preserved instead of being cleared

This skill now mirrors that model:

  • real active-account detection keys off the live openai-codex:default credential
  • snapshots keep a stable email-based identity instead of relying on ambiguous :default
  • switching rewrites :default across all agents while also retaining/upserting the email-specific profile entry
  • metadata migration repairs older snapshot records that incorrectly treated :default as a unique account id
  • email is the canonical human identity for deduplication; accountId may change when the same email moves to a different workspace/team, so same-email re-logins update the existing saved account instead of creating a duplicate

Notes

  • This skill stores sensitive OAuth tokens under ~/.openclaw/openai-codex-accounts/
  • Treat those files like credentials
  • Prefer list --verbose or status before making risky changes
  • Active account display is derived from the real OpenClaw auth file (~/.openclaw/agents/<agent>/agent/auth-profiles.json), then synced back into skill metadata. This avoids stale ACTIVE markers after manual openclaw models auth login or other out-of-band auth changes.
  • During periodic checks, if the real current OpenClaw auth is not present in the list yet, the skill will auto-enroll it as a new accountN snapshot and mark it active.

平台分布

OpenClaw

95.71%
按下载量换算3,966

安全审计

VirusTotal

可疑

ClawScan

可疑

Static analysis

通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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