libra: Evolving into an AI agent–native version control tools

by web3infra-foundation · Agent Tool · ★ 77

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

Security audit verdict: SAFE · quality 64/100

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.

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Quick Facts

Stars77
Forks161
LanguageRust
CategoryAgent Tool
LicenseMIT
Quality Score64/100
Last Updated2026-07-03
Created2025-09-12
Platformsrust
Est. Tokens~30k

About libra

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.

libra alternative? Top 6 similar tools

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.

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  • mcp-git-ingest by adhikasp · ⭐ 314

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  • lovcode by MarkShawn2020 · ⭐ 303

    A desktop companion app for AI coding tools. Browse Claude Code chat history, manage configurations, commands,

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How this security grade is produced

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:

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