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 beautifulSoup · AI Skill · ★ 60
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is speccoding-template safe to install? View the security audit →
SpecCoding Template 基于 Claude Code + OpenSpec + Superpowers 三件套的全栈 AI 开发模板。 让 AI 稳定交付全栈项目——告别"AI 改崩代码 / 失忆 / 跑偏"。 📣 扫码关注公众号 TangoAI实验室，每周更新 AI 开发实战干货 这是什么 一套可直接 Clone 即用的项目骨架，实现文章《让 AI 稳定交付全栈项目》里讲的完整工作流： ✅ 两级 Spec 体系： 管项目全局， 管单次变更 ✅ 两级分支模型： 承载一批需求， 隔离单次变更 ✅ 七阶段工作流：
| Stars | 60 |
| Forks | 11 |
| Category | AI Skill |
| License | MIT |
| Quality Score | 61.7934213284927/100 |
| Last Updated | 2026-05-03 |
| Created | 2026-04-18 |
| Platforms | claude-code |
| Est. Tokens | ~6k |
These tools work well together with speccoding-template for enhanced workflows:
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speccoding-template is 基于 Claude Code + OpenSpec + Superpowers 的全栈 AI 开发模板. It is categorized as a AI Skill with 60 GitHub stars.
You can find installation instructions and usage details in the speccoding-template GitHub repository at github.com/beautifulSoup/speccoding-template. The project has 60 stars and 11 forks, indicating an active community.
speccoding-template is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to speccoding-template on Agent Skills Hub include medharness, conductor-orchestrator-superpowers, claude-context-local. 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: