AIClient2API — security grade SAFE, quality 60/100

Security audit verdict: SAFE · quality 60/100

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 →

About AIClient2API

AIClient2API（A2）🚀 A powerful proxy that can unify the requests of various client-only large model APIs (Antigravity, Codex, Grok, Kiro ...), simulate requests, and encapsulate them into a local OpenAI-compatible interface. Docker Downloads 100k Ranked #2 on Trendshift [![Docker](https://img.shields.io/badge/d

Quick Facts

Compatible Skills

These tools work well together with AIClient2API for enhanced workflows:

• WindsurfAPI — semantic(0.24)+complementary+shared_fw(openai)+same_lang+similar_pop+shared_platform (66%)
• WebAI2API — semantic(0.16)+complementary+shared_fw(openai)+same_lang+similar_pop+shared_platform (63%)
• gcli2api — semantic(0.39)+complementary+shared_fw(openai)+similar_pop+shared_platform (62%)
• WindsurfPoolAPI — semantic(0.27)+complementary+shared_fw(openai)+same_lang+shared_platform (58%)

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Looking for a AIClient2API alternative? If you're comparing AIClient2API with other codex skill tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.

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• cockpit-tools by jlcodes99 · ⭐ 18.0k

  🚀 通用 AI IDE 账号管理工具：支持 Antigravity / Codex / GitHub Copilot / Windsurf / Kiro / Cursor / Gemini-cli / CodeBudd

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  AI coding platform for teams

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Frequently Asked Questions

How this security grade is produced

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:

• SlowMist agent-security taxonomy
• Liu et al., An Empirical Study of Agent Skill Security (2026)
• Our census dataset (DOI 10.5281/zenodo.21292799) · Hugging Face mirror
• Full methodology & who runs this