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 RealZST · MCP Server · ★ 433
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is HarnessKit safe to install? View the security audit →
HarnessKit English · 简体中文 One home for every agent. A free, open-source app to manage all your AI coding agents — desktop, CLI, or web. Why • Features • Get Started • Roadmap
| Stars | 433 |
| Forks | 38 |
| Language | Rust |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 66.7242123303122/100 |
| Open Issues | 5 |
| Last Updated | 2026-09-20 |
| Created | 2026-03-27 |
| Platforms | claude-code, cli, codex, gemini, mcp, rust |
| Est. Tokens | ~26k |
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HarnessKit is More than a skill manager — manage skills, MCP servers, plugins, hooks, CLIs, configs, memory & rules across every AI coding agent. 🌟 Star if you like it!. It is categorized as a MCP Server with 433 GitHub stars.
HarnessKit is primarily written in Rust. It covers topics such as ai-coding-agents, claude-code, cli-tools.
You can find installation instructions and usage details in the HarnessKit GitHub repository at github.com/RealZST/HarnessKit. The project has 433 stars and 38 forks, indicating an active community.
HarnessKit is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to HarnessKit on Agent Skills Hub include skill-manager, quint-code, compose-skill. 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: