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 Nayjest · Agent Tool · ★ 432
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is Gito safe to install? View the security audit →
Gito is an open-source AI code reviewer that works with any language model provider. It detects issues in GitHub pull requests or local codebase changes—instantly, reliably, and without vendor lock-in. Get consisten
| Stars | 432 |
| Forks | 40 |
| Language | Python |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 65.1854709030341/100 |
| Open Issues | 58 |
| Last Updated | 2026-09-05 |
| Created | 2025-04-30 |
| Platforms | python |
| Est. Tokens | ~17k |
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Gito is An AI-powered GitHub code review tool that uses LLMs to detect high-confidence, high-impact issues—such as security vulnerabilities, bugs, and maintainability concerns.. It is categorized as a Agent Tool with 432 GitHub stars.
Gito is primarily written in Python. It covers topics such as ai, ai-code-analysis, ai-code-review.
You can find installation instructions and usage details in the Gito GitHub repository at github.com/Nayjest/Gito. The project has 432 stars and 40 forks, indicating an active community.
Gito is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to Gito on Agent Skills Hub include ai-review, roam-code, lucidity-mcp. 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: