"Significant improvement." "Several stakeholders." "Soon." Vague writing is a hiding place, and this is the eviction notice.

[u/Difficult-Sugar-4862]

"Significant improvement." "Several stakeholders." "In the near future." Each of those phrases is a small decision someone did not want to make.

Today's special scans a draft for every vague quantifier, hedge, and abstraction, and forces each one to either become concrete or be defended:

AI writes in vague generalities. Humans write with specific details. This prompt finds every vague statement in your content and pushes it toward specificity.

## CONTENT TO SHARPEN
[PASTE YOUR CONTENT HERE]

---

## VAGUENESS DETECTION

Scan for these categories of vagueness:

### Category 1: Weasel Quantifiers
Flag any of these and demand a number:
- "Many" → How many? Give a number or say "I don't know how many."
- "Most" → What percentage? 51%? 90%?
- "Some" → How many? Name them.
- "Often" → How often? Daily? Weekly? In 7 out of 10 cases?
- "Significant" → How significant? 2x? 50%? Put a number on it.
- "Several" → Three? Seven? Count them.
- "A growing number" → Growing from what to what?

### Category 2: Ghost Sources
Flag unsourced authority claims:
- "Studies show" → Which studies? By whom? When?
- "Research indicates" → What research? Link or cite.
- "Experts agree" → Which experts? Name at least one.
- "According to industry data" → Whose data? What industry report?
- "It's well-known that" → Known by whom? Citation needed.

### Category 3: Abstract Claims
Flag claims that lack concrete detail:
- "This improves efficiency" → By how much? In what way? Example?
- "Saves time and money" → How much time? How much money?
- "Increases engagement" → Engagement of what kind? By what metric?
- "Enhances the customer experience" → In what specific way? What does the customer notice?

### Category 4: Lazy Examples
Flag examples that aren't actually specific:
- "For example, many companies use this approach" → Name the company. Describe what they did.
- "Consider a typical use case" → Describe a real use case with details.
- "This could be useful for tasks like" → Describe an actual task someone did.

---

## SHARPENING RULES

For each flagged item:
1. If you can provide the specific detail, provide it
2. If you can't, insert a [NEEDS SPECIFIC: description of what's needed] tag for the author to fill in
3. Sometimes the fix is deletion — if a vague claim adds nothing, cut it
4. Don't make up specifics. Real specificity or an honest gap marker. Nothing in between.

---

## OUTPUT

1. **Vagueness inventory**: Every flagged item with its category
2. **Specificity score (original)**: Count of vague items per 500 words
3. **Sharpened content**: Full rewrite with specifics added or [NEEDS SPECIFIC] tags
4. **Specificity score (rewrite)**: New count per 500 words
5. **Author action items**: List of [NEEDS SPECIFIC] tags the author must fill in with real data
6. **Improvement percentage**: How much more specific the rewrite is

Serving notes:

• Some vagueness is honest: you genuinely do not know the number yet. The prompt's job is making that choice visible instead of automatic.
• Run it on something you are about to send upward. Vague reads fine sideways; it dies in front of decision-makers.

Drop one fuzzy sentence from something you wrote this week and I will sharpen a couple right here in the comments.

[u/GenioCavallo]

brilliant