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 code-yeongyu · Codex Skill · ★ 3.7k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is lazycodex safe to install? View the security audit →
LazyCodex The one and only agent harness for complex codebases. Project memory, planning, execution, and verified completion inside Codex. What is this? · OmO · lazycodex.ai [!NOTE] [OmO] 60K Stars: the terrifying token burner has arrived in LazyCodex. Sisyphus Labs' OmO is the quality-obsessed agent harness whose public lore says it loved Anthropic models hard enough to get third-party clients blocked. Now that same OmO quality bar is available for Codex through LazyCodex. If you wanted OmO but did not want the setup ceremony, start here: Context: OmO 60K Stars on X 🚀 Install One line. No global install, no . Always use : This is shorthand for . For a fully
| Stars | 3,721 |
| Forks | 234 |
| Language | TypeScript |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 61.5539492436926/100 |
| Open Issues | 16 |
| Last Updated | 2026-10-03 |
| Created | 2026-05-25 |
| Platforms | claude-code, cli, codex, node |
| Est. Tokens | ~16k |
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lazycodex is The one and only agent harness for complex codebases. Project memory, planning, execution, and verified completion inside Codex.. It is categorized as a Codex Skill with 3.7k GitHub stars.
lazycodex is primarily written in TypeScript. It covers topics such as ai, ai-agents, claude.
You can find installation instructions and usage details in the lazycodex GitHub repository at github.com/code-yeongyu/lazycodex. The project has 3.7k stars and 234 forks, indicating an active community.
lazycodex is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to lazycodex on Agent Skills Hub include superset, happier, emdash. 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: