Fix a Vague Prompt
'Make it good', 'be detailed', 'keep it interesting' — vague prompts get vague output. The fix is mechanical: replace every fuzzy word with a checkable instruction.
'Write a blog post about X, make it engaging' is the most rewritten prompt on the internet. Here's its strong form — angle, reader, hook rule, and length.
Blog prompts fail in a predictable way: they name a topic and decorate it with adjectives, leaving the model to choose the angle, the reader, and the structure — which is why the output reads like everyone else's post on the topic. The rewrite takes those choices back. This resource loads the canonical weak blog prompt and shows its strong form: the adjectives become a hook rule and concrete requirements, and the missing reader, length, and coverage become explicit slots.
Rewrite the loaded prompt
'Engaging/interesting' becomes a hook rule, 'detailed' becomes a coverage slot, 'provide value' becomes an actionability instruction.
Fill reader and length
The two placeholders that kill genericness: who is reading, and how long. One line each.
Save the strong form
Topic swaps cleanly — the rewrite is your reusable blog prompt skeleton.
It converts the decoration into control. "Engaging/interesting" becomes a hook rule the model can actually execute, "detailed" becomes a coverage slot, and "provide value" becomes an actionability instruction — then it adds the missing reader and length slots. Same topic, but the angle stops defaulting to everyone else's post. You run the strengthened prompt in your own assistant.
Yes — that's the intended payoff. The strong form is a skeleton: the topic line swaps cleanly while the control lines (hook rule, reader, length, coverage) stay put, making it a reusable base for a content calendar. Turning it into a fill-in-the-blank template with named variables is a separate job the resource routes to the Prompt Template Builder.
'Make it good', 'be detailed', 'keep it interesting' — vague prompts get vague output. The fix is mechanical: replace every fuzzy word with a checkable instruction.
The fastest fix for mediocre AI output is rewriting the prompt: vague words become concrete instructions, hedges become commitments, and missing elements get filled.
Format, length, and exclusions are the three levers that make AI output land in usable shape. A rewrite shows how to retrofit them onto a prompt that has none.
See exactly what changed between v1 and v2 of a prompt — added, removed, and modified instructions, plus whether the revision reduced or introduced risk.
A side-by-side way to decide between two ChatGPT prompt drafts — scored on clarity, specificity, output control, and risk instead of gut feeling.
A set of before-and-after examples showing exactly what prompt cleanup removes — and what it deliberately leaves alone.
Rewrite a weak prompt into a stronger one — vague wording fixed, gaps filled, goal unchanged.