by libra-tools · Agent Tool · ★ 100
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.
The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.
| Stars | 100 |
| Forks | 161 |
| Language | Rust |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 65/100 |
| Open Issues | 427 |
| Last Updated | 2026-11-07 |
| Created | 2025-09-12 |
| Platforms | rust |
| Est. Tokens | ~30k |
Libra is a partial implementation of a Git client, developed in Rust. The goal is not to build a perfect, 100% feature-complete reimplementation of Git (if you want that, take a look at gitoxide). Instead, Libra is evolving into an AI agent–native version control system.
These tools work well together with libra for enhanced workflows:
Looking for a libra alternative? If you're comparing libra with other agent tool tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
Libra is evolving into an AI agent–native version control tools
better git cli for agents
🚀 UE5-UMG-MCP: A deep-focused MCP for Unreal Engine UMG layout. Designed to maximize AI efficiency within lim
🚀An SDK version manager for full-stack engineers
🔄 Git-friendly text synchronization for CODESYS. Export your project to ST files, edit with modern tools (or
Branchlet: A simple CLI Git worktree manager
Explore other popular agent tool tools:
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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: