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 arbiterForge · Claude Skill · ★ 145
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is codeArbiter safe to install? View the security audit →
Shared enforcement and project-context parity across Claude Code, Codex CLI, and Pi. One repository-owned governance layer for tests, reviews, security checks, decisions, and durable project context. You decide. codeArbiter enforces. Start learning · Install · Browse the reference Install it globally. It stays dormant until a repository explicitly opts in. Agentic coding, with a record codeArbiter is for teams and power users who let coding agent
| Stars | 145 |
| Forks | 7 |
| Language | Python |
| Category | Claude Skill |
| License | AGPL-3.0 |
| Quality Score | 61.7260150279927/100 |
| Open Issues | 33 |
| Last Updated | 2026-09-20 |
| Created | 2026-05-08 |
| Platforms | claude-code, cli, codex, python |
| Est. Tokens | ~19k |
These tools work well together with codeArbiter for enhanced workflows:
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codeArbiter is When you can't trust yourself with your code base, trust Arbiter.. It is categorized as a Claude Skill with 145 GitHub stars.
codeArbiter is primarily written in Python. It covers topics such as ai, ai-agents, ai-coding.
You can find installation instructions and usage details in the codeArbiter GitHub repository at github.com/arbiterForge/codeArbiter. The project has 145 stars and 7 forks, indicating an active community.
codeArbiter is released under the AGPL-3.0 license, making it free to use and modify according to the license terms.
The top alternatives to codeArbiter on Agent Skills Hub include smart-ralph, hcom, maestro-orchestrate. 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: