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 chaseai-yt · Claude Skill · ★ 1.6k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is claudex-loop safe to install? View the security audit →
Skills for working across Claude Code and Codex. This repository contains separate skills for choosing a model, making a one-off handoff, and running a complete development workflow. They share a repository and plugin distribution; Claudex Route is independent of the Claudex Loop workflow. Claudex Loop Claudex Loop gives a plan an independent review before implementation, then gives the code an independent inspection. Your current conversation handles requirements and coordination; the other provider challenges the plan with concrete evidence. T
| Stars | 1,643 |
| Forks | 158 |
| Language | Python |
| Category | Claude Skill |
| Quality Score | 66.327548744651/100 |
| Open Issues | 11 |
| Last Updated | 2026-09-06 |
| Created | 2026-06-05 |
| Platforms | claude-code, codex, python |
| Est. Tokens | ~8k |
These tools work well together with claudex-loop for enhanced workflows:
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Report issues related to MCP integration with Claude here.
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claudex-loop is Claude Code skill: four-phase plan hardening (recon, interrogate, Codex adversarial review, cross-model build & inspection) — two AI models harden your plan before a line of code exists, then swap job. It is categorized as a Claude Skill with 1.6k GitHub stars.
claudex-loop is primarily written in Python.
You can find installation instructions and usage details in the claudex-loop GitHub repository at github.com/chaseai-yt/claudex-loop. The project has 1.6k stars and 158 forks, indicating an active community.
The top alternatives to claudex-loop on Agent Skills Hub include claude-code-showcase, claude-codex-settings, digital-marketing-pro. 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: