Skill UI

Guides building reliable autonomous agents by covering agent loops, goal decomposition, reflection, and tooling patterns while stressing guardrails, human review, and auditability to curb compounding failure rates in production.

Autonomous agents are AI systems capable of independently decomposing goals, planning actions, executing tools, and self-correcting without constant human guidance. This skill focuses on ensuring reliability in agent loops like ReAct and Plan-Execute, emphasizing goal decomposition and reflection patterns. It highlights that compounding error rates can kill autonomy, advocating for constrained, domain-specific agents over general autonomy. Build for reliability first.

This skill covers designing reliable autonomous AI systems that independently decompose goals, plan actions, and execute tools. It focuses on agent loops like ReAct and Plan-Execute, goal decomposition, reflection patterns, and ensuring production reliability. Key insight is managing compounding error rates where high per-step success rates drop significantly over multiple steps.