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 luoyuctl · Codex Skill · ★ 131
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is agenttrace safe to install? View the security audit →
AgentTrace Local-first TUI and reports for AI coding-agent session history, cost, tokens, time, and slow-run diagnosis. English | 简体中文 <img src="assets/readme-real-run.gif" alt="agenttrace run
| Stars | 131 |
| Forks | 10 |
| Language | Rust |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 68.6808914517635/100 |
| Open Issues | 7 |
| Last Updated | 2026-09-11 |
| Created | 2026-05-01 |
| Platforms | claude-code, cli, codex, gemini, rust |
| Est. Tokens | ~24k |
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agenttrace is Local-first Rust TUI/CLI for auditing AI coding-agent sessions: cost, tokens, latency, failures, and health｜本地优先 Rust TUI/CLI，审计 AI 编程 Agent 会话的成本、Token、延迟、失败与健康度. It is categorized as a Codex Skill with 131 GitHub stars.
agenttrace is primarily written in Rust. It covers topics such as ai-agent-observability, ai-agents, ai-cost-tracking.
You can find installation instructions and usage details in the agenttrace GitHub repository at github.com/luoyuctl/agenttrace. The project has 131 stars and 10 forks, indicating an active community.
agenttrace is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to agenttrace on Agent Skills Hub include agf, toktrack, catchup. 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: