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agents-autogpt

Run goal-driven autonomous agent loops — decomposing objectives, executing tool chains, self-critiquing, and iterating until done. Use when exploring what fully autonomous task execution looks like and its limits.

skills/agents-autogpt/SKILL.md

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# Goal-Driven Autonomous Loops

The autonomous-loop pattern: give an agent a goal, and let it plan, act, observe, and replan in a 
loop until the goal is met or it gives up. It's the purest form of "agent" — and the best teacher 
of why autonomy needs guardrails.

## Overview

The loop has four phases: plan (decompose the goal into steps), act (execute tools), observe (read 
results), and critique (evaluate progress and adjust). Memory holds the plan and findings across 
iterations. The loop terminates on goal completion, a step budget, or a give-up condition. This 
pattern shines for open-ended research and exploration — and fails instructively at long-horizon 
reliability, which is exactly what studying it teaches.