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 AVADSA25 · Agent Tool · ★ 106
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is codec safe to install? View the security audit →
Sovereign AI Workstation The open-source AI workstation for macOS, powered by CODEC Your voice. Your computer. Your rules. avadigital.ai · opencodec.org · Get Started · Support · Enterprise CODEC turns a Mac into a voice-controlled AI workstation that runs 100% on your machine. Speak. See the screen. Click anywhere by voice. Run agent crews. Plug into Claude, Cursor, or VS Code as an MCP server — and let them drive your Mac back. Open source · MIT · no cloud required. <img src="https://img.shields.io/badge/skills-76-
| Stars | 106 |
| Forks | 9 |
| Language | Python |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 56.4481384913361/100 |
| Last Updated | 2026-09-16 |
| Created | 2026-03-24 |
| Platforms | python |
| Est. Tokens | ~25k |
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codec is Open-Source Intelligent Command Layer. It is categorized as a Agent Tool with 106 GitHub stars.
codec is primarily written in Python. It covers topics such as llm-agent, llm-agent-framework, local-ai.
You can find installation instructions and usage details in the codec GitHub repository at github.com/AVADSA25/codec. The project has 106 stars and 9 forks, indicating an active community.
codec is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to codec on Agent Skills Hub include guaardvark, ENZO, edsl. 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: