autostar

autostar is an Execution & autonomous loops skill for AI agents, published by chrisvoncsefalvay in the autostar repository on GitHub. Skillspace rates autostar D (63/100) and it passed the safety scan; the rating is based on static analysis only.

Generalised autonomous optimisation loop — soft RLVR for any artifact a user can measure. Use this skill whenever a user wants to iteratively improve an artifact — code, prompts, documents, configs, designs, content — by running structured experiments, evaluating results against a multi-dimensional rubric, and learning from each attempt. Triggers include: "optimise this", "keep improving until it's good", "run experiments on", "autoresearch", "iterate on this overnight", "try different approaches and pick the best", or any request implying repeated evaluate-and-improve cycles. Also use when the user wants to improve a system prompt, a data pipeline, a writing style, or any artifact where quality can be decomposed into measurable tracks. For inference optimisation tasks (model latency, throughput, quantization, GPU deployment), a* delegates the low-level tuning to AITune while maintaining quality tracking and learning.

Grade

D

Quality

63 / 100

Safety

Passed

GitHub stars

38

Unproven: rated by static analysis only, not yet compared head-to-head.

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