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 f · Agent Tool · ★ 560
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is agentlytics safe to install? View the security audit →
Agentlytics Your Cursor, Devin, Claude Code sessions — analyzed, unified, tracked. One command to turn scattered AI conversations from 17 editors into a unified analytics dashboard.Sessions, costs, models, tools — finally in one place. 100% local. The Problem You switch between Cursor, Devin, Claude Code, VS Code Copilot, and more — each with its own siloed conversation history. ✗ Sessions scattered across editors, no unified view ✗ No idea how much you're spending on AI tokens ✗ Can't compare which editor is more effective ✗ Can't search across all your AI conversations ✗ No way to share session context with your team ✗ No unified view of your plans, credits, and rate lim
| Stars | 560 |
| Forks | 84 |
| Language | JavaScript |
| Category | Agent Tool |
| Quality Score | 68.6044775630512/100 |
| Open Issues | 26 |
| Last Updated | 2026-08-03 |
| Created | 2026-03-07 |
| Platforms | claude-code, node, vscode |
| Est. Tokens | ~15k |
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agentlytics is Comprehensive analytics dashboard for AI coding agents — Cursor, Windsurf, Claude Code, VS Code Copilot, Zed, Antigravity, OpenCode, Command Code. It is categorized as a Agent Tool with 560 GitHub stars.
agentlytics is primarily written in JavaScript. It covers topics such as agentlytics, ai-coding-assistant, analytics.
You can find installation instructions and usage details in the agentlytics GitHub repository at github.com/f/agentlytics. The project has 560 stars and 84 forks, indicating an active community.
The top alternatives to agentlytics on Agent Skills Hub include memorix, palot, omega-memory. 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: