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 cristianoliveira · Agent Tool · ★ 294
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is funzzy safe to install? View the security audit →
Funzzy () One reliable edit loop for developers and coding agents. Funzzy is a fast Rust file watcher and local workflow runner. You define checks in one YAML file. Funzzy runs matching jobs when files change. It reports the state of each run, so you do not have to inspect logs or reuse an old result. Why Funzzy? One workflow: use the same YAML file for watch mode, local runs, editors, CI, and agents. Predictable execution: Funzzy runs jobs in declared order. Named groups enable parallel work. Cancellation stops the complete process tree. Long-running services: a readiness check confirms that a service started correctly. The service can then stay active. Exact feedback: local tools can use a
| Stars | 294 |
| Forks | 11 |
| Language | Rust |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 63.6318904365138/100 |
| Open Issues | 2 |
| Last Updated | 2026-09-19 |
| Created | 2016-03-21 |
| Platforms | cli, rust |
| Est. Tokens | ~23k |
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funzzy is Gives developers and coding agents one reliable edit loop. It is categorized as a Agent Tool with 294 GitHub stars.
funzzy is primarily written in Rust. It covers topics such as agentic-coding, ai-agents, ai-tools.
You can find installation instructions and usage details in the funzzy GitHub repository at github.com/cristianoliveira/funzzy. The project has 294 stars and 11 forks, indicating an active community.
funzzy is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to funzzy on Agent Skills Hub include crit, Claude-Skills, claude-brain. 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: