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.
Generic prompts produce generic output. Specificity is added in slots — audience, context, named requirements — and a rewrite shows exactly which slots yours is missing.
When output feels generic, the prompt usually lacks anchors: who it's for, what situation it serves, and what concretely must appear. Adding specificity isn't about writing more — it's about filling the right slots. This resource loads a prompt that names a topic and nothing else; the specificity-focused rewrite adds audience and context slots and converts every soft ask into a named requirement, while leaving your actual subject untouched.
Rewrite with Increase Specificity
The mode adds audience and context slots, and rewrites 'relevant' and 'valuable' into concrete instructions.
Fill the two slots
Audience and context are one line each — they're also the two highest-leverage lines in the prompt.
Compare before and after
The topic didn't change. What changed is that the output now has a reader and a reason.
It does not; it leaves your subject untouched and fills slots around it. In the loaded example ("Write an article about remote work"), Increase Specificity mode adds audience and context slots and rewrites soft asks like "relevant" and "valuable" into named requirements, so the topic stays remote work; the output now has a reader and a reason. You still run the filled prompt in your own assistant.
Audience and context, each one line, and the rewrite calls audience the single highest-leverage line because it constrains tone, depth, and examples at once. The mode adds both as slots for you to fill; the soft-to-named conversion, turning "valuable" into a checkable requirement, does the rest. You still run the filled prompt in your own assistant.
'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.