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 ARPAHLS · Agent Tool · ★ 71
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is skillware safe to install? View the security audit →
A Python framework for modular, self-contained skill management for machines. Mission • Architecture • Quick Start • Documentation • Contributing • Comparison • Changelog • Contact Skillware is an open-source framework and registry for modular, actionable Agent capabilities. It treats Skills as installable content, decoupling capability from intelligence. Just as installs software and installs libraries, installs know-how for AI agents. "I know Kung Fu." - Neo Mission The AI ecosystem is fragmented. Developers often re-invent tool definitions, system prompts, and safety rules for every project. Skillware supplies a standard to package capabilities into self-contained, installabl
| Stars | 71 |
| Forks | 54 |
| Language | Python |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 65.9019432112309/100 |
| Open Issues | 64 |
| Last Updated | 2026-09-20 |
| Created | 2026-01-20 |
| Platforms | python |
| Est. Tokens | ~16k |
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skillware is A Python framework for modular, self-contained skill management for machines.. It is categorized as a Agent Tool with 71 GitHub stars.
skillware is primarily written in Python. It covers topics such as agent-skills, ai, ai-agents.
You can find installation instructions and usage details in the skillware GitHub repository at github.com/ARPAHLS/skillware. The project has 71 stars and 54 forks, indicating an active community.
skillware is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to skillware on Agent Skills Hub include guaardvark, pydantic-ai-todo, mcp-server. 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: