{
  "id": 5803873,
  "title": "How I Turned a Research Paper into an AI Skill with NotebookLM",
  "url": "https://urgent.news/2026/09/05/how-i-turned-a-research-paper-into-an-ai-skill-with-notebooklm",
  "topic": "ai",
  "section": "AI",
  "published": "2026-09-05T17:28:05.000Z",
  "source": {
    "name": "Dev.to",
    "slug": "dev-to",
    "url": "https://dev.to/rahmanfrr/how-i-turned-a-research-paper-into-an-ai-skill-with-notebooklm-1okp"
  },
  "original_language": "en",
  "account": "I aimed to craft a reusable AI skill from a research paper, rather than relying on vague instructions. I began by uploading the paper to NotebookLM, treating it as an AI research assistant. Instead of seeking a general summary, I asked targeted questions like: What are the main principles? Which ideas can become writing rules? What patterns lead to repetitive or unnatural-sounding text? This process allowed me to separate valuable insights from academic minutiae. The next step involved converting the paper's concepts into clear instructions for the AI. For instance, an academic discussion on varying sentence structure was transformed into a direct rule: Vary sentence length and structure. The skill had to be specific, easy to follow, concise, and practical. Organizing the rules into a structured skill.md file proved essential. The layout included sections like Role, Core Principles, Editing Rules, Audience Modes, Prohibited Patterns, Editing Workflow, and Final Checklist. This structure ensured the skill was readable and applicable. Including examples alongside the rules made them easier to understand and apply. For example, it was demonstrated how to improve an AI-generated sentence by removing unnecessary phrases and adopting more straightforward language. After crafting the initial skill, I tested it on various types of writing, such as blog posts, technical explanations, academic paragraphs, and marketing content. Each test revealed issues like overly casual tone, loss of technical terms, or the AI following the rules too rigidly, resulting in a monotonous writing style. I addressed these problems by adding a crucial rule: do not alter, invent, or remove research claims, citations, data, or important qualifications. This ensured the AI humanized the text without losing its integrity. NotebookLM proved valuable in understanding and organizing the research paper, helping me identify key ideas, compare sections, extract examples, and ask follow-up questions. However, it was clear that NotebookLM did not replace the editing process; I still needed to determine which ideas were relevant, how detailed the instructions should be, and how to tailor the skill for different audiences. Ultimately, the skill transformed into a practical manual for specific writing tasks. The article was written using the skill.md file developed through this process.",
  "summary": "I wanted to create a reusable AI skill, but I did not want to write vague instructions based on guesswork. I wanted the skill to have a clear foundation. So I started with a research paper and used NotebookLM to understand its main ideas before turning them into a practical skill.md file. Here is the process I followed. Why I started with a research paper AI instructions often sound useful but…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}