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 hmenzagh · Claude Skill · ★ 115
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is CCMeter safe to install? View the security audit →
A terminal dashboard for Claude Code usage analytics Track tokens, costs, code generation, and efficiency, all from your terminal. Quick start Overview CCMeter reads your local Claude Code session data and renders an interactive TUI dashboard. Data refreshes every 5 minutes (manual reload with ). Metrics & analytics Cost tracking — per-model USD breakdown (Opus, Sonnet, Haiku) via built-in pricing tables Token analytics — input, output, and prompt cache usage over time Code metrics — lines suggested, accepted, added, and deleted, with acceptance rate Active time estimation — approximates how long you actually spent working on each project from session activity Efficiency score — tokens per line o
| Stars | 115 |
| Forks | 6 |
| Language | Rust |
| Category | Claude Skill |
| Quality Score | 71.8750633679379/100 |
| Last Updated | 2026-05-09 |
| Created | 2026-04-05 |
| Platforms | claude-code, rust |
| Est. Tokens | ~76k |
These tools work well together with CCMeter for enhanced workflows:
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CCMeter is Deep analytics and session insights for your Claude Code usage. It is categorized as a Claude Skill with 115 GitHub stars.
CCMeter is primarily written in Rust. It covers topics such as analytics, claude, claude-code.
You can find installation instructions and usage details in the CCMeter GitHub repository at github.com/hmenzagh/CCMeter. The project has 115 stars and 6 forks, indicating an active community.
The top alternatives to CCMeter on Agent Skills Hub include claude-view, tokenscope, ccboard. 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: