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 androidZzT · Codex Skill · ★ 112
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is cc-statistics safe to install? View the security audit →
cc-statistics The only AI coding tracker that unifies Claude Code, Gemini CLI, Codex CLI, and Cursor — in one native macOS app. Track every token, cost, and session across all your AI tools. 100% local. Zero dependencies. Why? • Features • Screenshots • Quick Start &bul
| Stars | 112 |
| Forks | 14 |
| Language | Swift |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 61.3376563849374/100 |
| Last Updated | 2026-08-07 |
| Created | 2026-03-17 |
| Platforms | claude-code, cli, codex, gemini |
| Est. Tokens | ~17k |
These tools work well together with cc-statistics for enhanced workflows:
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cc-statistics is AI Coding stats dashboard — track costs, tokens, and efficiency across Claude Code / Gemini CLI / Codex / Cursor. It is categorized as a Codex Skill with 112 GitHub stars.
cc-statistics is primarily written in Swift. It covers topics such as ai-coding, claude-code, cli.
You can find installation instructions and usage details in the cc-statistics GitHub repository at github.com/androidZzT/cc-statistics. The project has 112 stars and 14 forks, indicating an active community.
cc-statistics is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to cc-statistics on Agent Skills Hub include codexU, toktrack, agent-island. 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: