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 tmseidel · Agent Tool · ★ 158
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is ai-git-bot safe to install? View the security audit →
AI-Git-Bot 🌐 Languages: English · 中文 · 한국어 · 日本語 Automate the necessary-but-uncomfortable parts of software development — directly inside the Git tools your team already uses. Every team has a list of "we know we should be doing this" engineering chores: writing a properly scoped issue before coding starts, adding a regression test for the bug you just fixed, re-reviewing a PR after the third force-push, tearing down a stale preview environment. These chores are necessary but uncomfortable — and they get cut first under deadline pressure. AI-Git-Bot turns those chores into repeatable, automated workflows that live natively inside Gitea, GitHub, GitHub Enterprise, GitLab, and Bitbucket Cloud — triggered by the events your team is already producing (issue assigned, PR opened, reviewer re-requested, mentioned in
| Stars | 158 |
| Forks | 37 |
| Language | Java |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 64.7295597370214/100 |
| Open Issues | 5 |
| Last Updated | 2026-09-10 |
| Created | 2026-03-31 |
| Platforms | java |
| Est. Tokens | ~18k |
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ai-git-bot is The self-hosted AI workflow automation platform for Git repositories.. It is categorized as a Agent Tool with 158 GitHub stars.
ai-git-bot is primarily written in Java. It covers topics such as ai, ai-tools, anthropic.
You can find installation instructions and usage details in the ai-git-bot GitHub repository at github.com/tmseidel/ai-git-bot. The project has 158 stars and 37 forks, indicating an active community.
ai-git-bot is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to ai-git-bot on Agent Skills Hub include ai-review, open-jet, c4-genai-suite. 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: