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 TravisLeeeeee · Agent Tool · ★ 110
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is awesome-openclaw-personas safe to install? View the security audit →
Awesome OpenClaw Personas Languages: English · 中文 · Français · Deutsch · Русский · 日本語 · Italiano · Español 214 ready-to-use AI agent personas for OpenClaw — each one a complete specialist with real SOPs, decision frameworks, and structured outputs. Clone a folder, get an expert. What is an OpenClaw Persona? OpenClaw is an AI agent platform that turns large language models into autonomous assistants. A persona is a complete configuration package that gives your OpenClaw agent a specific professional identity — not just a single prompt, but a full set of structured files: Capabilities, frameworks, output templates — what
| Stars | 110 |
| Forks | 18 |
| Category | Agent Tool |
| Quality Score | 56.0014565607237/100 |
| Open Issues | 2 |
| Last Updated | 2026-04-08 |
| Created | 2026-03-25 |
| Est. Tokens | ~113k |
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awesome-openclaw-personas is 🧠 Curated collection of 214+ best OpenClaw personas — weekly updated by Deskclaw.net from GitHub & community. AI, productivity, dev, marketing, finance & more.. It is categorized as a Agent Tool with 110 GitHub stars.
You can find installation instructions and usage details in the awesome-openclaw-personas GitHub repository at github.com/TravisLeeeeee/awesome-openclaw-personas. The project has 110 stars and 18 forks, indicating an active community.
The top alternatives to awesome-openclaw-personas on Agent Skills Hub include agent-skills, creative-director-skill, .claude. 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: