Flagged: sudo usage. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by vivekchand · Codex Skill · ★ 423
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is clawmetry safe to install? View the security audit →
🦞 ClawMetry See your agent think. Real-time observability for 12 AI agent runtimes: OpenClaw, NVIDIA NemoClaw, Claude Code, OpenAI Codex & 8 more. One dashboard for your whole agent fleet. 🌐 Read this in: English · 简体中文 · 日本語 · 한국어 · Español · [Português (BR)
| Stars | 423 |
| Forks | 71 |
| Language | Python |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 70.3678852200822/100 |
| Open Issues | 61 |
| Last Updated | 2026-10-03 |
| Created | 2026-02-13 |
| Platforms | claude-code, cli, codex, gemini, python |
| Est. Tokens | ~18k |
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clawmetry is See your agent think. Zero-config observability & governance for 30 AI agent runtimes: Claude Code, OpenAI Codex, Hermes, OpenClaw & 26 more. Live token costs, sessions, tool calls, crons.. It is categorized as a Codex Skill with 423 GitHub stars.
clawmetry is primarily written in Python. It covers topics such as agent-monitoring, ai-agent, ai-agents.
You can find installation instructions and usage details in the clawmetry GitHub repository at github.com/vivekchand/clawmetry. The project has 423 stars and 71 forks, indicating an active community.
clawmetry is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to clawmetry on Agent Skills Hub include agent-skills, agent-deck, Overture. 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: