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 Nanako0129 · Codex Skill · ★ 400
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is syrtis safe to install? View the security audit →
Syrtis AI token usage & quota monitor for the macOS menu bar — native Swift, Liquid Glass. English · 繁體中文 · 简体中文 Syrtis is a free, open-source macOS menu-bar app that reads the session logs your AI coding tools already write to disk and displays your tokens, costs, and subscription quotas. It supports 25+ tools—including Claude Code, Codex, Cursor, OpenCode, Gemini CLI, Copilot, Kiro, and Antigravity—completely on-device, with no Dock icon, no telemetry, no user account, and no cloud sync. Until version 2.0, the app was called TokenBar on macOS; upgrading preserves your
| Stars | 400 |
| Forks | 38 |
| Language | Swift |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 67.4221689750124/100 |
| Open Issues | 8 |
| Last Updated | 2026-10-03 |
| Created | 2026-06-10 |
| Platforms | claude-code, codex |
| Est. Tokens | ~17k |
These tools work well together with syrtis for enhanced workflows:
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syrtis is AI token usage & quota monitor for the macOS menu bar — native Swift, Liquid Glass, 3D contribution graph. Tracks Claude Code, Codex, Cursor, OpenCode & 25+ agents locally.. It is categorized as a Codex Skill with 400 GitHub stars.
syrtis is primarily written in Swift. It covers topics such as ai-usage, claude-code, codex.
You can find installation instructions and usage details in the syrtis GitHub repository at github.com/Nanako0129/syrtis. The project has 400 stars and 38 forks, indicating an active community.
syrtis is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to syrtis on Agent Skills Hub include TokenEater, poirot, swiftui-design-skill. 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: