ai-slop-detector

Detect low-quality AI-generated code by scanning for six cardinal signs: incorrect logic, inefficiency, poor readability, security vulnerabilities, supply chain risks (slopsquatting), and context gaps. The Skill identifies weak naming, hollow comments, hallucinated dependencies, and insecure patterns across languages and ecosystems to surface actionable remediation guidance.

Yes. The Skill integrates with CI/CD workflows by proposing gating rules and automation hooks to catch AI slop before merge. It works with linting and review tooling to gate low-quality patterns and governance processes, preventing tech debt from AI-assisted development.

Security scanning identifies vulnerabilities, insecure patterns, and supply chain risks including slopsquatting (fake dependencies) and hallucinated imports. The Skill provides remediation plans for each detected security issue to guide human review and code fixes.

Run a codebase scan to identify AI slop patterns—incorrect logic, inefficiency, readability problems, and security gaps. The Skill produces a risk-based remediation plan that integrates into code review workflows for human-driven remediation of flagged issues.

Yes. The Skill detects AI slop across languages and ecosystems, identifying universal patterns like weak naming, marketing buzzwords in documentation, and insecure code structures regardless of language or framework used.

After detection, the Skill provides actionable remediation guidance for each supply chain risk. Findings integrate with governance processes and review tooling to enable human teams to audit, replace, or remove problematic dependencies before deployment.