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 MageByte-Zero · Codex Skill · ★ 809
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is spec-superflow safe to install? View the security audit →
spec-superflow 源码级融合 OpenSpec 规划引擎 + Superpowers 执行纪律的 AI 编程工作流插件 为什么需要它 | 使用方式 | English | Showcase | Skills | 快速开始 | 工作流 | FAQ 为什么需要它 用 AI 写代码时，最常碰到两个失控点： 还没想清楚要做什么，AI 就开始写代码。 你说了句"帮我加个权限控制"，它就开始改几十个文件。改到一半才发现 —— 到底要 RBAC 还是 ABAC？ 规划文档写得明明白白，但执行阶段还是会跑偏。 proposal 写了、design 画了，但实现过程中没人盯着测试、没人卡 review，等到合并才发现行为不对。 spec-superflow 在两个失控点之间用源码级的引擎 + 桥接协议建立起一道硬墙： 先把需求问清楚 - 把意图沉淀为正式工件（Schema 引擎验证格式）- 把规划压缩成执行契约 - 以 TDD + SDD + Review Gate 三重纪律强制执行 - 处理执行中的阻塞 - 审查每批产出 - 验证后收口 - 同步 delta spec 防止规范腐烂。 它不是把 OpenSpec 和 Superpowers 并排安装再手工拼接，而是把两者的核心引擎和能力吸收进一个自包含的工作流 ow
| Stars | 809 |
| Forks | 81 |
| Language | JavaScript |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 62.3698151356239/100 |
| Open Issues | 7 |
| Last Updated | 2026-09-20 |
| Created | 2026-06-26 |
| Platforms | claude-code, cli, codex, gemini, node |
| Est. Tokens | ~17k |
These tools work well together with spec-superflow for enhanced workflows:
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spec-superflow is 源码级融合 OpenSpec 规划引擎 + Superpowers 执行纪律的 AI 编程工作流插件。17 平台支持，9 skills，Spec-first，契约驱动。. It is categorized as a Codex Skill with 809 GitHub stars.
spec-superflow is primarily written in JavaScript. It covers topics such as ai-coding, amazon-q, claude-code.
You can find installation instructions and usage details in the spec-superflow GitHub repository at github.com/MageByte-Zero/spec-superflow. The project has 809 stars and 81 forks, indicating an active community.
spec-superflow is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to spec-superflow on Agent Skills Hub include ccmanager, memorix, openspec-plus. 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: