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Codex introduces a new feature that automatically analyzes user historical memory with a single prompt, extracts repetitive workflows, and converts them into evolvable skills, automating daily repetitive tasks.
This paper systematically evaluates model-generated skills for language agents across the full lifecycle of experience generation, extraction, and consumption, finding that skills are beneficial on average but exhibit non-trivial negative transfer, leading to a meta-skill that improves skill quality.