Flagged: sudo usage. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by Neo-Isshin · Codex Skill · ★ 50
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🔒 Is TokenClock safe to install? View the security audit →
简体中文 · English 🕰️ TokenClock A native Liquid Glass desktop clock for your AI coding usage Track Claude Code, Codex, Antigravity(parse by CLI IDE App), OpenCode, and 10 more tools on one living glass dial — entirely on your Mac. Native Liquid Glass on macOS 26+ · wallpaper-aware refraction · ambient tint · adaptive contrast · always-on-top 🧊 Liquid Glass is the interface, not a skin TokenClock turns macOS 26's native Liquid Glass into a useful, glanceable instrument. The clock disc refracts the desktop behind it, picks up a subtle theme tint, and automatically switches its ink contrast to stay readable as the wallpa
| Stars | 50 |
| Forks | 1 |
| Language | C |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 61.4897800681802/100 |
| Last Updated | 2026-10-01 |
| Created | 2026-07-12 |
| Platforms | claude-code, cli, codex, gemini |
| Est. Tokens | ~18k |
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TokenClock is Native Liquid Glass AI token tracker for macOS. Breakdown into sessions/models/tools.. It is categorized as a Codex Skill with 50 GitHub stars.
TokenClock is primarily written in C. It covers topics such as ai-coding, claude-code, developer-tools.
You can find installation instructions and usage details in the TokenClock GitHub repository at github.com/Neo-Isshin/TokenClock. The project has 50 stars and 1 forks, indicating an active community.
TokenClock is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to TokenClock on Agent Skills Hub include swiftui-design-skill, cc-statistics, WhereMyTokens. 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: