No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by bob-zebedy · Codex Skill · ★ 92
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is CodexBar safe to install? View the security audit →
CodexBar 在 macOS 菜单栏一眼看清 Codex 简体中文 | English 功能 性能报告 CodexBar 是面向 macOS 15 及更高版本的菜单栏 App，用于集中展示 Codex 账户、额度、Token 用量和实时任务状态。 它可以在任务完成、等待批准或额度变化时提醒你，也能只在 Codex 任务运行期间自动防止系统睡眠。 功能 账户与额度一目了然 展示当前 Codex 账户和套餐 展示全部额度窗口、剩余比例和重置时间 展示可用积分和留存重置 支持自动重置，可设置在留存重置过期前 15 分钟到 6 小时执行，默认提前 30 分钟；计划到点时可唤醒 Mac，并在执行前重新确认可用状态 可通过菜单栏圆弧直接显示所选额度窗口的剩余比例 看见自己的 Codex 使用节奏 展示累计 Token、单日峰值和连续使用天数 展示最长任务时长 通过 30 周热力图回顾每日 Token 用量 开启 CodexBar Hook 后可查看会话、对话轮次、工具调用和子 Agent 等每日统计 不错过正在发生的任务 菜单栏人物徽章区分运行中、等待批准、最近完成和最近终止任务 主面板展示当前任务、项目、模型、推
| Stars | 92 |
| Forks | 4 |
| Language | Swift |
| Category | Codex Skill |
| License | GPL-3.0 |
| Quality Score | 56.4322183849278/100 |
| Last Updated | 2026-09-22 |
| Created | 2026-06-10 |
| Platforms | cli, codex |
| Est. Tokens | ~15k |
These tools work well together with CodexBar for enhanced workflows:
Looking for a CodexBar alternative? If you're comparing CodexBar with other codex skill tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
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CodexBar is CodexBar 是一个 macOS 菜单栏应用，用于查看本机 Codex 账号状态、额度、Token 用量、详细统计信息. It is categorized as a Codex Skill with 92 GitHub stars.
CodexBar is primarily written in Swift. It covers topics such as appkit, codex, codex-cli.
You can find installation instructions and usage details in the CodexBar GitHub repository at github.com/bob-zebedy/CodexBar. The project has 92 stars and 4 forks, indicating an active community.
CodexBar is released under the GPL-3.0 license, making it free to use and modify according to the license terms.
The top alternatives to CodexBar on Agent Skills Hub include codexU, agent-island, Hopet. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: