Six Checks Before You Trust an AI Agent Skill

Short summary

The article proposes six review checks for evaluating AI agent skills (reusable instruction files for coding agents): verify the skill inspects real targets before acting, defines inspectable completion conditions, sets explicit boundaries on dangerous actions, orders actions by risk with rollback paths, validates at the correct layer (local vs production), and requires reports that separate facts from assumptions. These checks help teams avoid trusting polished but unsafe or unverifiable agent workflows.

• •Six checks: real-target discovery, inspectable outputs, explicit boundaries, risk-ordered actions, correct-layer validation, fact-vs-assumption reporting
• •Strong skills establish what is true before acting; weak skills jump straight to actions
• •Reports must separate observed facts, evidence, assumptions, and unresolved risks

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