Six Security Checks to Evaluate Before Trusting Any AI Agent Skill

AI agent skills, stored as reusable instruction files like SKILL.md, are growing in popularity for automating coding and deployment tasks across sessions. However, a well-formatted skill can still be unsafe, vague, or unverifiable, raising concerns for both third-party and internally written workflows. Experts recommend checking that a skill performs real discovery before acting, defines inspectable outputs as evidence of success, and sets explicit hard boundaries around destructive actions like deleting data or force-pushing to production. Strong skills also order operations by risk level, preferring reversible steps first, and must distinguish between local validation and live-target verification. A skill that cannot cleanly recover from a wrong hypothesis or fails to confirm changes on the actual production environment should not be trusted without revision.