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 garrytan · Codex Skill · ★ 172
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is alphaclaw safe to install? View the security audit →
AlphaClaw The ultimate OpenClaw harness. Deploy in minutes. Stay running for months. Observability. Reliability. Agent discipline. Zero SSH rescue missions. AlphaClaw wraps OpenClaw with a convenient setup wizard, self-healing watchdog, Git-backed rollback, and full browser-based observability. Ships with anti-drift prompt hardening to keep your agent disciplined, and simplifies integrations (e.g. Google Workspace, Google Pub/Sub, Telegram Topics, Slack, Discord) so you can manage multiple agents from one UI instead of config files. First deploy to first message in under five minutes. <a href="https://railway.com/deploy/openclaw-fast-start?referralCode=jcFhp&utmmedium=
| Stars | 172 |
| Forks | 35 |
| Language | JavaScript |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 65.471586462705/100 |
| Open Issues | 27 |
| Last Updated | 2026-09-27 |
| Created | 2026-04-04 |
| Platforms | cli, node |
| Est. Tokens | ~17k |
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alphaclaw is The ultimate setup harness for OpenClaw. Deploy in minutes. Stay running for months. No CLI required.. It is categorized as a Codex Skill with 172 GitHub stars.
alphaclaw is primarily written in JavaScript.
You can find installation instructions and usage details in the alphaclaw GitHub repository at github.com/garrytan/alphaclaw. The project has 172 stars and 35 forks, indicating an active community.
alphaclaw is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to alphaclaw on Agent Skills Hub include ai-maestro, upskill, skills. 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: