Beyond Linters: Catching Systematic Failures in AI-Generated Code

Large language models rapidly generate working code, but systematic failure modes—hallucinated APIs, premature abstractions, and mock abuse—consistently evade traditional linters and code review. Guard Skills addresses this gap with specialized quality gates designed to detect LLM-specific failure patterns before code reaches production. As AI-assisted development becomes mainstream, this second-pass verification layer is becoming essential infrastructure for maintaining code quality at scale.