by memorax-ai · Codex Skill · ★ 2.0k
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npm install -g @memorax/memorax-code --foreground-scriptsTaken from the project's README on GitHub. Check the security audit before running it.
None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.
| Stars | 2,004 |
| Forks | 68 |
| Language | JavaScript |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 73/100 |
| Open Issues | 24 |
| Last Updated | 2026-11-04 |
| Created | 2026-08-01 |
| Platforms | claude-code, codex, node |
| Est. Tokens | ~15k |
Never lose context. Never start over. Beyond code, it remembers how your architecture evolves and how your engineering unfolds. English · 简体中文 Make Every Interaction the Starting Point for the Next Coding agents are good at the task in front of them, but a new session often starts without the architecture, failed attempts, repository rules, or working preferences established before it.
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Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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: