Flagged: dynamic eval(). Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by Dicklesworthstone · Agent Tool · ★ 303
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is ultimate_bug_scanner safe to install? View the security audit →
🔬 Ultimate Bug Scanner v5.0 The AI Coding Agent's Secret Weapon: Flagging Likely Bugs for Fixing Early On Or via Homebrew (macOS/Linux): Just want it to do everything without confirmations? Live life on the edge with easy-mode to auto-install every dependency, accept all prompts, detect local coding agents, and wire their quality guardrails with zero extra questions: Note: Windows users must run the installer one-liner from within Git Bash, or use WSL for Windows. </
| Stars | 303 |
| Forks | 44 |
| Language | Python |
| Category | Agent Tool |
| Quality Score | 62.0038113888286/100 |
| Open Issues | 4 |
| Last Updated | 2026-09-22 |
| Created | 2025-11-16 |
| Platforms | cli, python |
| Est. Tokens | ~25k |
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ultimate_bug_scanner is Static analysis tool that catches 1000+ bug patterns across all popular programming languages, with auto-wiring into AI coding agent quality guardrails. It is categorized as a Agent Tool with 303 GitHub stars.
ultimate_bug_scanner is primarily written in Python. It covers topics such as agent-tools, ai-agents, bash.
You can find installation instructions and usage details in the ultimate_bug_scanner GitHub repository at github.com/Dicklesworthstone/ultimate_bug_scanner. The project has 303 stars and 44 forks, indicating an active community.
The top alternatives to ultimate_bug_scanner on Agent Skills Hub include roam-code, plankton, uxc. 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: