Microsoft's SkillOpt boosts GPT-5.5 by using nothing but a trained Markdown file
Quick Answer
Microsoft, in collaboration with three Chinese universities, has introduced SkillOpt, a method that enhances GPT-5.5's performance on procedural tasks by approximately 23 points using a trained Markdown file.
Quick Take
Microsoft, in collaboration with three Chinese universities, has introduced SkillOpt, a method that enhances GPT-5.5's performance on procedural tasks by approximately 23 points using a trained Markdown file. This optimization technique is transferable across various models and environments, including Codex and Claude Code.
Key Points
- SkillOpt optimizes AI instruction documents using traditional model training principles.
- A single Markdown file can significantly enhance GPT-5.5's procedural task performance.
- The performance boost of 23 points is notable for AI agent efficiency.
- SkillOpt's methodology is applicable across different AI models and environments.
- Collaboration with Chinese universities highlights international research efforts in AI.
Article Excerpt
From source RSS / original summaryMicrosoft and three Chinese universities have developed SkillOpt, a method that optimizes instruction documents for AI agents using principles from traditional model training. A simple Markdown file is enough to boost GPT-5. 5 by about 23 points on procedural tasks, and the same file transfers across models and agent environments like Codex and Claude Code. The article Microsoft's SkillOpt boosts GPT-5. 5 by using nothing but a trained Markdown file appeared first on The Decoder.
Reader Mode unavailable (could not extract clean content).
Want this in your inbox every morning?
Daily brief at your local 8am — bilingual EN/中文, free.
More from The Decoder
See more →
OpenAI models now available on Amazon Web Services
OpenAI has launched GPT-5.5, GPT-5.4, and Codex on Amazon Bedrock, matching its own pricing. Currently, these models are available only in the US across commercial and government AWS regions, with usage contributing to existing AWS contracts.
