Loop Design + Review

Premise. An LLM is a feed-forward system: prompt in → tokens out, with no built-in "steer toward the goal" across turns. To make it behave like a goal-oriented system, you wrap a feedback loop around it. This skill helps you write that loop correctly and review it so it won't run away.

When to use / not

Use it when:

• You want to hand a repeating task to an agent that runs over and over (write→test, test→fix, fix→verify…).
• You already have a loop and worry it spins, cheats, or runs a wrong answer to completion.

Don't use it for:

• A one-off task → just do it; don't wrap a loop around it.
• A plain timer / poll → use /loop; no design needed.
• How to wire the loop architecture (pipelines → DAGs, long-run recovery) → that's the mechanism layer; see autonomous-loops / continuous-agent-loop. This skill only covers "is the goal right, and will it run away" — it does not re-explain mechanism.

Red-line premise: two levels of feedback