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 vava-nessa · Codex Skill · ★ 2.8k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is free-coding-models safe to install? View the security audit →
free-coding-models Find the fastest free coding model in seconds Track 191 models across 20 trusted free or free-limited AI providers in real time Install Free API endpoints to your favorite AI coding tools: OpenCode CLI / Desktop / WebUI, OpenClaw, Crush, Goose, Aider, Kilo CLI, Qwen Code, OpenHands, Amp, Hermes, Continue, Cline, Xcode, Pi and more... Use Kimi K2, DeepSeek V3, GPT-OSS, Qwen3, MiniMax M3, GLM, Llama 4, Gemma 4, Devstral and more — for free create a free account on one of the providers <a href="#-why-this-too
| Stars | 2,786 |
| Forks | 297 |
| Language | HTML |
| Category | Codex Skill |
| Quality Score | 64.0523454105238/100 |
| Open Issues | 3 |
| Last Updated | 2026-09-29 |
| Created | 2026-02-20 |
| Platforms | cli |
| Est. Tokens | ~26k |
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free-coding-models is Find, benchmark and install in CLI 170+ FREE coding LLM models across 15+ providers in real time. It is categorized as a Codex Skill with 2.8k GitHub stars.
free-coding-models is primarily written in HTML. It covers topics such as ai, deepseek, free.
You can find installation instructions and usage details in the free-coding-models GitHub repository at github.com/vava-nessa/free-coding-models. The project has 2.8k stars and 297 forks, indicating an active community.
The top alternatives to free-coding-models on Agent Skills Hub include tokscale, kiro-gateway, deepchat. 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: