A great knowledge base article gets a stuck user un-stuck in under a minute. That means answering the exact question they searched, structuring the content so they can skim to the relevant step, and writing in plain language without jargon. This builder turns your topic and article type into a prompt that makes an LLM produce a scannable, correctly structured draft you can edit and publish.
How it works
You enter the topic, your product name, and the precise user question the article should answer, then choose the article type. A how-to produces a goal-oriented intro plus numbered steps with expected results. A reference produces a definition, then a structured description of options or settings. A troubleshooting guide starts from the symptom and walks through likely causes and fixes in order of probability. The prompt instructs the model to use descriptive headings, short paragraphs, second-person active voice, and callouts for tips and warnings, and to end with related-articles suggestions. You can set a reading level to keep the language accessible. Everything is generated locally.
Tips and examples
Write the user question the way a real customer would type it into search (“how do I export my invoices to CSV”), not the way your team names the feature internally — that single choice drives findability. Match the type to the intent: do not write a reference article when the user has a task to complete. For consistent voice across your help centre, paste one or two of your best existing articles into the prompt as style examples; the model will mimic their tone far more reliably than any adjective you supply. Always edit the draft against the real product UI before publishing — an AI can describe a plausible flow that differs from your actual buttons and labels.