by chattymin · Codex Skill · ★ 542
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brew install --cask chattymin/tap/poke-token-barTaken from the project's README on GitHub. Check the security audit before running it.
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. Full audit →
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 | 542 |
| Forks | 163 |
| Language | Swift |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 65/100 |
| Open Issues | 50 |
| Last Updated | 2026-11-04 |
| Created | 2026-06-15 |
| Platforms | claude-code, cli, codex, gemini |
| Est. Tokens | ~19k |
PokeTokenBar Your AI coding tokens, hatched into Pokémon — right in your menu bar. English · 한국어 · 日本語 PokeTokenBar turns the AI coding tokens you're already burning — Claude Code, Codex, Gemini CLI, Antigravity, OpenCode, Hermes Agent, Cursor, Grok CLI, Copilot CLI & Kiro CLI — into a growing Pokémon companion in your macOS menu bar.
These tools work well together with PokeTokenBar for enhanced workflows:
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Cover your Mac's screen with a hotkey while AI agents keep running, even with the lid closed. The covered scre
macOS 原生 AI 额度监控与用量分析工具，实时监控 Codex、Claude Code、Cursor、Antigravity 剩余用量与本地 Token 消耗和费用。 Native macOS menu bar a
A keyboard-first menubar app to monitor and jump between AI coding sessions — minimum setup required.
Native macOS app to monitor AI usage limits and watch your coding sessions live
Monitor all your Claude/Codex usage limits in real-time from your macOS menu bar - supports 5-hour, 7-day, ext
AI Coding stats dashboard — track costs, tokens, and efficiency across Claude Code / Gemini CLI / Codex / Curs
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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: