by composio-community · Codex Skill · ★ 1.2k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
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 | 1,188 |
| Forks | 168 |
| Language | JavaScript |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 77/100 |
| Open Issues | 5 |
| Last Updated | 2026-07-25 |
| Created | 2026-02-08 |
| Platforms | claude-code, node |
| Est. Tokens | ~17k |
Secure OpenClaw A personal 24x7 AI assistant that runs on your messaging platforms. Send a message on WhatsApp, Telegram, Signal, or iMessage and get responses from Claude with full tool access, persistent memory, scheduled reminders, and integrations with 500+ apps. Get your free API key to get started → Table of Contents Requirements [I
Looking for a secure-openclaw alternative? If you're comparing secure-openclaw 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.
A complete security skill suite for OpenClaw, Hermes, PicoClaw and NanoClaw agents (and variants). Protect you
Multi-AI documentation for OpenClaw: architecture, security audits, deployment guide
Unbrowse - Reverse engineer any website so that your agents can access its APIs directly
The forge that forges itself. Self-writing meta-extension for OpenClaw.ai
🛰️ Track token usage across AI coding agents from your terminal. 🏅 Global leaderboard with trillions of toke
🦞 OpenClaw (Clawdbot/Moltbot) 汉化版 - 开源个人 AI 助手中文版 | Claude/ChatGPT LLM 接入 | WhatsApp/Telegram/Discord 多平台 | 每
Explore other popular codex skill tools:
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: