Researchers propose a new framework called SkillForge to help large language models resolve specific software issues. Unlike existing approaches that rely on historical data or exploration costs, SkillForge proactively acquires project-specific knowledge from the repository itself by synthesizing test-covered core functionalities and resolving synthetic issues. This approach improves issue resolution performance over strong baselines in both open-source and closed-source models. --- Why it matters: This matters to AI engineers because it tackles a common challenge in software development: language models often struggle with specific project knowledge, leading to suboptimal solutions. SkillForge's proactive acquisition of project-specific knowledge can improve downstream software issue resolution, making it an important contribution to the field. Source: https://arxiv.org/abs/2608.18933