by aqua5230 · Codex Skill · ★ 345
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git clone https://github.com/aqua5230/usage.gitTaken from the project's README on GitHub.
None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. 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 | 345 |
| Forks | 66 |
| Language | Python |
| Category | Codex Skill |
| License | AGPL-3.0 |
| Quality Score | 67/100 |
| Last Updated | 2026-11-06 |
| Created | 2026-05-17 |
| Platforms | claude-code, cli, codex, python |
| Est. Tokens | ~15k |
usage 繁體中文 · English 是一個 macOS menu bar（螢幕右上角的選單列）小工具，把 Claude Code 跟 Codex 的用量釘在你的螢幕右上角。點開可以看到 Session、Weekly、各專案用量（今日 / 7 日 / 月），以及今日 token 用量與成本估算。 不呼叫 Anthropic / OpenAI 的 API（接口）、也不讀 Keychain（macOS 內建的密碼保險箱），所以不會發生「自己每分鐘 ping 一次也算用量」這種事。 它怎麼拿到你的用量數字 用量數字來自 Claude Code 跟 Codex 在你本機留下的檔案，不呼叫 Anthropic / OpenAI 的 API。唯一的例外：估算 Codex 成本時需要 token 單價表，如果本機沒有快取（），會嘗試從公開的 LiteLLM 價格表 下載一次並存起來，7...
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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: