by lwh0630 · Codex Skill · ★ 203
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
docker compose up -d # set TOKENBAR_TOKEN (and optionally TOKENBAR_READ_TOKEN) in .env
git clone https://github.com/lwh0630/TokenBar.git
Taken from the project's README on GitHub.
Flagged: sudo usage. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.
The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.
| Stars | 203 |
| Forks | 13 |
| Language | Dart |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 62/100 |
| Last Updated | 2026-11-03 |
| Created | 2026-10-24 |
| Platforms | claude-code, codex |
| Est. Tokens | ~21k |
TokenBar Every AI quota, one glance away. An open-source, cross-platform monitor for AI usage limits, balances and reset times. Runs on Windows, macOS, Linux, Android and iOS. English | 简体中文 Inspired by CodexBar for macOS. TokenBar brings the same idea to Windows, Android, Linux and iOS (and ships a macOS build too), and covers 52 services. Why TokenBar See everything in one place.
These tools work well together with TokenBar for enhanced workflows:
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Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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: