by knostic · Codex Skill · ★ 91
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
git clone https://github.com/knostic/openclaw-shield
Taken from the project's README on GitHub.
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.
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 | 91 |
| Forks | 13 |
| Language | TypeScript |
| Category | Codex Skill |
| License | Apache-2.0 |
| Quality Score | 74/100 |
| Open Issues | 8 |
| Last Updated | 2026-05-12 |
| Created | 2026-02-04 |
| Platforms | node |
| Est. Tokens | ~4k |
OpenClaw Shield - Alpha By Knostic openclaw-shield: Security plugin for OpenClaw. Prevents your AI agent from leaking secrets, exposing PII, or executing destructive commands. CRITICAL: OpenClaw gets updated constantly, and without community updates, it won't stay effective for more than mere days. already we had to update it several times.
These tools work well together with openclaw-shield for enhanced workflows:
Looking for a openclaw-shield alternative? If you're comparing openclaw-shield 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.
User-friendly orchestrator for OpenClaw
Save 120+ Hours of Setup Pain (I did it for you) – Launch Your OpenClaw Agent Teams with 1 Command (15+ Recipe
AgentWard – Built for all, hardened for OpenClaw.
Official MemOS Cloud plugin for OpenClaw. Enables long-term memory for agents by recalling context before exec
terminally online
The forge that forges itself. Self-writing meta-extension for OpenClaw.ai
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: