by bitsky-tech · Agent Tool · ★ 69
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claude plugin install AmphiLoop
git clone https://github.com/bitsky-tech/AmphiLoop.gitTaken from the project's README on GitHub. Check the security audit before running it.
None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.
| Stars | 69 |
| Forks | 2 |
| Language | Shell |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 65/100 |
| Open Issues | 1 |
| Last Updated | 2026-05-23 |
| Created | 2026-03-19 |
| Platforms | cli |
| Est. Tokens | ~12k |
AmphiLoop English | 中文 AmphiLoop, short for Amphibious Loop, is a new methodology, technology stack, and toolchain for building AI agents. It enables tasks to be described and orchestrated using natural language, with an “Explore → Code → Verify” loop guiding code generation and build. The resulting artifacts are capable of automatically switching between workflow mode and agent mode at runtime.
These tools work well together with AmphiLoop for enhanced workflows:
Explore other popular agent tool tools:
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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: