Flagged: sudo usage. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by KlaatAI · Codex Skill · ★ 357
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is klaatcode safe to install? View the security audit →
Klaat Code The terminal-native AI coding agent, powered by Klaatu smart model routing. Claude Code-grade accuracy, at a fraction of the cost — and it's reproducible, not a marketing claim. What is KlaatAI? KlaatAI is an AI platform built around Klaatu-o1, a small, fast, agentic router model. Instead of sending every request
| Stars | 357 |
| Forks | 136 |
| Language | TypeScript |
| Category | Codex Skill |
| Quality Score | 70.4636701206116/100 |
| Open Issues | 28 |
| Last Updated | 2026-08-16 |
| Created | 2026-07-17 |
| Platforms | claude-code, cli, gemini, node |
| Est. Tokens | ~19k |
These tools work well together with klaatcode for enhanced workflows:
Looking for a klaatcode alternative? If you're comparing klaatcode with other codex skill tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
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全网最全的、持续更新的、最火爆的 100+ 人格 蒸馏skills 合集｜ 多agent系统 ｜名人/导演/天涯大神/古籍/二次元/职场/情感全品类
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klaatcode is Open-source AI coding agent for the terminal. Claude Code-grade accuracy with smart model routing — uses the right AI model for each task, cutting costs 10x. Supports Claude, GPT, Gemini, DeepSeek & m. It is categorized as a Codex Skill with 357 GitHub stars.
klaatcode is primarily written in TypeScript. It covers topics such as agentic-ai, ai, ai-agents.
You can find installation instructions and usage details in the klaatcode GitHub repository at github.com/KlaatAI/klaatcode. The project has 357 stars and 136 forks, indicating an active community.
The top alternatives to klaatcode on Agent Skills Hub include gptree, agent-skills-collection, claudekit. 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: