Resource
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.
Add Success Criteria to a Prompt
If you can't say what makes the output right, the model can't either. Success criteria turn 'make it good' into a checkable definition of done.
Overview
The quiet defect in most prompts: no definition of done. 'Good', 'high quality', and 'useful' feel like criteria but check nothing. A success criterion is a sentence you could evaluate the output against — 'a reader can act on it without follow-up questions', 'every claim has a number or a source'. This resource loads a prompt whose only quality bar is the word 'good' and rewrites it so the bar becomes explicit, checkable, and yours.
How to use this resource
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Rewrite the loaded prompt
'Good' becomes a success-criteria slot; 'covers what they need to know' becomes a coverage list you name.
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Write the criterion as a test
Good test: 'a new hire can complete day one without asking their manager anything in the guide'. Bad test: 'comprehensive'.
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Reuse the pattern
Any prompt with an approval step deserves a criteria line — it's the line reviewers actually use.
Why This Works
- A checkable criterion changes both sides: the model optimizes toward it and you evaluate against it
- Criteria written as tests catch the gap between plausible and correct
- The rewrite leaves the criterion as a placeholder because 'done' is a decision, not a default
Best for
- Prompts whose output gets reviewed or approved by someone
- Recurring prompts where 'is this right?' keeps coming up
- Deliverables with a real reader who can be failed
Not for
- Scoring two prompts against each other — that's the Prompt Comparator
- Prompts for pure exploration where 'done' genuinely doesn't apply
Use cases
- Making AI output evaluable instead of just plausible
- Aligning a team on what a shared prompt is supposed to produce
- Converting quality adjectives into acceptance checks
FAQ
How does this rewriter sharpen a prompt that just says 'make it good'?
It turns the vague bar into a checkable one. On the loaded onboarding-guide prompt, 'good' becomes a success-criteria slot and 'covers what they need to know' becomes a coverage list you name. The prompt-rewriter reshapes the pasted text into that structure; it doesn't write the onboarding guide itself — you run the rewritten prompt in your assistant afterward.
Why does the rewrite leave the success criterion blank instead of filling one in?
Because "'done' is a decision, not a default." The rewrite leaves the criterion as a placeholder for you to write as a test — a good one is "a new hire can complete day one without asking their manager anything in the guide," a bad one is "comprehensive." The tool exposes the slot; the standard your reviewers actually use is yours to define.
More resources from Prompt Rewriter
Resource
Rewrite an AI Prompt to Get Better Output
The fastest fix for mediocre AI output is rewriting the prompt: vague words become concrete instructions, hedges become commitments, and missing elements get filled.
Resource
Add Output Control to Any Prompt
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.
Resources that pair well
Resource
Compare Two Versions of a Prompt
See exactly what changed between v1 and v2 of a prompt — added, removed, and modified instructions, plus whether the revision reduced or introduced risk.
Resource
Compare Two ChatGPT Prompts
A side-by-side way to decide between two ChatGPT prompt drafts — scored on clarity, specificity, output control, and risk instead of gut feeling.
Resource
Prompt Cleanup Examples (Before & After)
A set of before-and-after examples showing exactly what prompt cleanup removes — and what it deliberately leaves alone.
Related tools
Tool
Prompt Rewriter
Rewrite a weak prompt into a stronger one — vague wording fixed, gaps filled, goal unchanged.
Guides for this resource
Guide
How to Make AI Follow Acceptance Criteria
The output reads well and answers the question, so you almost ship it — then you notice it broke a rule you cared about and skipped a section you needed. "Looks good" was never the test. Here's how to give AI the acceptance criteria up front and check the output against them before you rely on it.
Guide
How to Make AI Generate Cleaner First Drafts With Fewer Revisions
"Write a professional email" comes back smooth, generic, and aimed at the wrong reader — so you burn three rounds feeding in details you should have led with. Here's how to write a short first-draft brief up front, so the draft lands closer to what you needed.
Guide
Use AI to Turn Requirements Into Acceptance Criteria
Hand AI a vague requirement like "improve onboarding" and it fills the blanks with its own guesses — nobody said what "done" means. Here's how to turn a requirement into observable, testable acceptance criteria you can review before any implementation.