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 hyqibot · Codex Skill · ★ 118
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is token-free-openclaw safe to install? View the security audit →
iClaw [English] [日本語] 爱你所爱，如影随形。 永久免 token 费的 openclaw；三个重磅 Skill 大幅提升桌面执行能力；无需安装，开箱即用；支持微信、钉钉等多端接入控制。 宣传海报 同一版式的可编辑页面见 （克隆仓库后，用本地浏览器打开该文件即可完整预览；在 GitHub 网页上点开 HTML 一般为源码视图）。 核心特色： 永久免 token 费 — 通过 Web 模型调用技术，实现调用各大热门模型全免费（不消耗API token）, ChatGPT、Claude、Gemini、DeepSeek、千问、豆包、Kimi、智谱清言均可免费。 支持微信、钉钉 — 支持微信、钉钉等多端接入控制。 无需安装，开箱即用 — 鉴于多数ai项目部署复杂，本项目采取无需安装的模式，拷贝项目直接运行exe即可（win10以上系统，安装Chrome），提供官方参考视频，关注抖音号98806056998获取。 Skill 能力扩张 — 兼容所有 OpenClaw 技能，并提供更强的 Skill 扩展能力：例如全自动智能选股、智能交易等。 AlphaHYQi 支持（新版计划） — AlphaHYQi比iclaw更智能,比openc
| Stars | 118 |
| Forks | 32 |
| Language | Python |
| Category | Codex Skill |
| License | Apache-2.0 |
| Quality Score | 59.8787573469521/100 |
| Open Issues | 1 |
| Last Updated | 2026-08-23 |
| Created | 2026-04-12 |
| Platforms | claude-code, gemini, python |
| Est. Tokens | ~15k |
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token-free-openclaw is 永久免 token 费的 openclaw， ChatGPT、Claude、Gemini、DeepSeek、千问、豆包、Kimi、智谱清言均可免费；三个重磅 Skill 大幅提升桌面执行能力；无需安装，开箱即用；支持微信、钉钉等多端接入控制。兼容所有 OpenClaw 技能，并提供更强的 Skill 扩展。交流社区：钉钉群165930016082，需更快更稳定能接入Claude code的版本私. It is categorized as a Codex Skill with 118 GitHub stars.
token-free-openclaw is primarily written in Python. It covers topics such as openclaw, token, token-free.
You can find installation instructions and usage details in the token-free-openclaw GitHub repository at github.com/hyqibot/token-free-openclaw. The project has 118 stars and 32 forks, indicating an active community.
token-free-openclaw is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to token-free-openclaw on Agent Skills Hub include codex_register, auto-commenter, n8n-claw. 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: