Prompt2Skill: Unsupervised Skill Optimization From Natural Language Instructions

arXiv:2609.38593 · cs.CL, cs.AI · Submitted 2026-09-29 · Read on arXiv

cs.CL, cs.AI

Submitted: 2026-09-29

Updated: 2026-09-29

Code: https://github.com/Arstanley/Prompt2Skill

Terminology

• Benchmark — 23× in this paper · explained in 2 episodes
• Verification — 15× in this paper · explained in 2 episodes
• Core — 14× in this paper · explained in 2 episodes
• Alignment — 10× in this paper · explained in 1 episode
• Adaptation — 8× in this paper · explained in 1 episode
• Agent Skills — 7× in this paper · explained in 1 episode
• Ablation — 4× in this paper · explained in 1 episode
• Generative AI — 4× in this paper · explained in 2 episodes
• Accuracy — 3× in this paper · explained in 1 episode
• Consistency — 3× in this paper · explained in 3 episodes
• Failure Modes — 3× in this paper · explained in 3 episodes
• Fine-Tuning — 3× in this paper · explained in 5 episodes
• Multi-Agent Framework — 2× in this paper · explained in 3 episodes
• Synthetic Data Generation — 2× in this paper · explained in 5 episodes
• Trace — 2× in this paper · explained in 2 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Actor — 1× in this paper · explained in 3 episodes
• Aggregation — 1× in this paper · explained in 1 episode
• Axioms — 1× in this paper · explained in 2 episodes
• Benchmarking — 1× in this paper · explained in 3 episodes
• Conservation Laws — 1× in this paper · explained in 3 episodes
• Data Provenance — 1× in this paper · explained in 2 episodes
• Exponential Generating Functions — 1× in this paper
• Grounding — 1× in this paper · explained in 3 episodes
• Iterative Refinement — 1× in this paper · explained in 3 episodes
• LLM judge — 1× in this paper · explained in 2 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Multi-Agent System — 1× in this paper · explained in 6 episodes
• Nash Equilibrium — 1× in this paper · explained in 2 episodes
• Provenance — 1× in this paper · explained in 4 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Structural Integrity — 1× in this paper · explained in 3 episodes
• Structured Reasoning — 1× in this paper · explained in 3 episodes
• Thinking mode — 1× in this paper · explained in 2 episodes

Sources

• SearchQA: A New Q&A Dataset Augmented with Context from a Search Engine
• MLZero: A Multi-Agent System for End-to-end Machine Learning Automation
• SkillsBench: Benchmarking How Well Agent Skills Work Across Diverse Tasks
• SpreadsheetBench: Towards Challenging Real World Spreadsheet Manipulation
• Trace2Skill: Distill Trajectory-Local Lessons into Transferable Agent Skills
• Automatic Prompt Optimization with "Gradient Descent" and Beam Search
• SQuAD: 100,000+ Questions for Machine Comprehension of Text
• AutoML-Agent: A Multi-Agent LLM Framework for Full-Pipeline AutoML
• Prompt2Model: Generating Deployable Models from Natural Language Instructions
• Agent Skills for Large Language Models: Architecture, Acquisition, Security, and the Path Forward
• SkillOpt: Executive Strategy for Self-Evolving Agent Skills

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