ai-coding-welfare: Claude Code / Codex 免费额度导航:收录 AI Coding 公益站 / 中转站,自动巡检可用性、签到额度、邀请返利

by Q-shuang-dot · Codex Skill · ★ 65

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Security audit verdict: SAFE · quality 61/100

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.

ai-codinganthropicapi-relayawesome-listchinaclaude-codecodexdevtoolsfree-apifree-tier

Quick Facts

Stars65
Forks2
LanguageJavaScript
CategoryCodex Skill
LicenseMIT
Quality Score61/100
Open Issues1
Last Updated2026-10-22
Created2026-09-16
Platformsclaude-code, codex, node
Est. Tokens~24k

About ai-coding-welfare

AI 福利站 · Claude Code / Codex 免费额度白嫖导航 免费额度 · 白嫖 Claude Code / Codex / Cursor 的中转与公益站合集 · 每日签到领福利 AgentRouter 注册 · DoCode 注册 · 年华 API 注册 · 肖恩AI 注册 · api456.me 注册 · JustDoWork 注册 · Matrix 注册 · SeekAi 注册 · Long的AI 注册 · 新疆幻城网安 注册 🚀 一分钟上车(福利站) 下面两张表都是

Compatible Skills

These tools work well together with ai-coding-welfare for enhanced workflows:

  • awesome-ai-api-proxy — semantic(0.43)+complementary+shared_fw(anthropic,openai)+rare_topics+similar_pop+shared_platform (80%)
  • reverse-check — semantic(0.36)+complementary+shared_fw(anthropic,openai)+rare_topics+similar_pop+shared_platform (78%)
  • ai-welfare-hub — semantic(0.49)+shared_fw(anthropic,openai)+rare_topics+same_lang+similar_pop+shared_platform (77%)

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Looking for a ai-coding-welfare alternative? If you're comparing ai-coding-welfare 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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  • LoongPort by SailingLoong · ⭐ 138

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How this security grade is produced

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:

View on GitHub → Browse Codex Skill tools