Prompt templates and their placeholders
Each entry carries two pieces of text that do different jobs. The description explains, in ordinary English, what the prompt produces and what you have to supply. The prompt itself is the instruction you paste in, and it is written with bracketed placeholders — [PRODUCT NAME], [TARGET AUDIENCE], [TONE] — marking the inputs to swap for your own details. That structure is what separates a usable prompt template from a screenshot of somebody else's chat: you can see the moving parts before you run it, and change them.
Prompt engineering without the theory
You do not need to study prompt engineering to get something out of this library, although reading a few entries in one category teaches the shape of a good instruction faster than most courses do. Beginner prompts run as written and need one or two inputs. Intermediate prompts, which are the bulk of the collection, expect several inputs and a decision about tone or format. Advanced prompts assume you will rework the structure around your own workflow rather than run them as they stand.
Free AI prompts, kept accurate
New prompts are added as they are written and checked, across writing, marketing, SEO, sales, customer support, data analysis, image generation, coding and study. Entries that stop working well as the models change are revised rather than left in place — sorting by Recently Updated shows what has been touched most recently. If a prompt returns something generic, the usual cause is a placeholder left unfilled, and the questions beside this text cover the rest.