antislop

name	antislop
description	Detect and fix AI writing patterns (slop). 45+ patterns across 3 severity tiers with scoring and an editor mode that fixes problems directly.
version	1.0.2
tags	["writing","ai-detection","humanizer","content-quality","editing"]
tool_agnostic	true
authors	["Anders Hybertz"]

Trigger conditions

Load this skill when the user says any of: "check for slop", "does this sound like AI", "humanize this", "AI audit", "slop check", "clean up AI writing", antislop, or any request to detect or remove artificial-sounding patterns. Also use proactively before publishing any AI-assisted content.

---

The 30-Second Test

The Horoscope Test:

"Could anyone have written this, for anyone?"

If yes, it's slop. Like a horoscope — technically applicable to everyone, resonant with no one.

What fails:

• Vague claims without specific examples
• Advice that applies universally without context
• Content missing the author's distinct perspective
• Writing that could have any byline

What passes:

• Specific tools, dates, outcomes mentioned
• Personal observations grounded in experience
• Opinions that not everyone would agree with
• Details only this author would know

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How It Works

1. Run the Horoscope Test — could anyone have written this for anyone?
2. Scan for patterns — 45+ known AI tells across 6 categories
3. Calculate slop score — tiered severity with quantifiable scoring
4. Apply fixes — editor mode rewrites problems, not just flags them
5. Report changes — before/after for every fix applied

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Detection Patterns

Tier 1: Almost Always AI (Remove Immediately)

These phrases are so strongly associated with AI that their presence alone suggests unedited output.

Pattern	Example	Fix
Delve	"Let's delve into..."	Remove or replace with direct statement
Game-changer	"This game-changing approach..."	Describe the actual impact
Revolutionary	"A revolutionary new method..."	State what it actually does
Unlock potential	"Unlock your potential..."	Remove entirely
Leverage (as verb)	"Leverage these insights..."	"Use"
It's worth noting	"It's worth noting that..."	Just state the thing
That matters because	"That matters because the protocols..."	Remove; the preceding sentence should carry its own weight, or restructure to lead with the reason
This one matters a lot	"This one matters a lot for application teams."	Remove; if it matters, the content shows it — announcing it is the tell
Moreover/Furthermore	"Moreover, this approach..."	Remove or use "Also"
Today's digital landscape	"In today's digital landscape..."	Remove
Cutting-edge	"Cutting-edge solutions..."	Remove
Pivotal moment	"Marking a pivotal moment in..."	State what happened
Tapestry (abstract)	"A rich tapestry of influences..."	Remove or be specific
Intricate/intricacies	"The intricacies of..."	"Details of" or remove
Showcase (as verb)	"Showcasing their commitment..."	"Shows" or describe what happened
Vibrant	"A vibrant community of..."	Remove or use specific detail
Interplay	"The interplay between X and Y..."	"How X and Y affect each other"
Garner	"Garnering attention from..."	"Got attention from" or be specific
Align with	"Aligning with broader trends..."	State the actual relationship

Research evidence:

• Finnish study (56,878 essays): "delve" usage increased 10.45x post-ChatGPT
• Georgia Tech (168.3M articles): "delve" went from 0.31 to 7.9 per 1,000 papers in Q1 2024
• Biomedical study: co-usage of "delve," "realm," "underscore" increased up to 85x in 2023–2024

Tier 2: Suspicious When Repeated

Problematic when overused or clustered.

Pattern	Example	Fix
Here's the thing	Used repeatedly	Keep first, vary subsequent
At the end of the day	"At the end of the day..."	Remove
The bottom line	"The bottom line is..."	Just state it
Let's dive in	"Without further ado, let's dive in"	Remove
Comprehensive and thorough	Paired adjectives	Pick one
Simple and straightforward	Paired adjectives	Pick one
In this post, we'll cover	Template opening	Remove
By the end of this article	Promise opener	Remove

Tier 3: Watch for Clusters

Fine individually, problematic together.

Pattern	Example	Fix
However/But	Every paragraph starts this way	Vary transitions
Firstly/Secondly/Thirdly	Enumerated points	Use natural flow
Moving forward	"Moving forward, we'll..."	Remove
Robust/Seamless/Scalable	Corporate buzzwords	Use specific terms
Stakeholder	"Key stakeholders..."	Name them or say "people"

---

Content Patterns

#	Pattern	Before	After
1	Significance inflation	"marking a pivotal moment in the evolution of..."	"was established in 1989 to collect statistics"
2	Notability name-dropping	"cited in NYT, BBC, FT, and The Hindu"	"In a 2024 NYT interview, she argued..."
3	Superficial -ing analyses	"symbolizing... reflecting... showcasing..."	Remove or expand with actual sources
4	Promotional language	"nestled within the breathtaking region"	"is a town in the Gonder region"
5	Vague attributions	"Experts believe it plays a crucial role"	"according to a 2019 survey by..."
6	Formulaic challenges	"Despite challenges... continues to thrive"	Specific facts about actual challenges
7	Outline-like conclusions	"Challenges" section ending with optimistic outlook	Remove or replace with actual analysis

---

Language Patterns

#	Pattern	Before	After
8	Copula avoidance	"serves as... features... boasts..."	"is... has..."
9	Negative parallelisms	"It's not just X, it's Y"	State the point directly
10	Rule of three	"innovation, inspiration, and insights"	Use natural number of items
11	Synonym cycling	"protagonist... main character... central figure..."	"protagonist" (repeat when clearest)
12	False ranges	"from the Big Bang to dark matter"	List topics directly
13	Clinical formality	"individuals" / "utilize" / "implement"	"people" / "use" / "do"

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Style Patterns

#	Pattern	Before	After
14	Em dash overuse	"institutions--not the people--yet this continues--"	Use commas or periods
15	Boldface overuse	"OKRs, KPIs, BMC"	"OKRs, KPIs, BMC"
16	Emoji headers	"🎯 Target Goal / 💡 Key Insight"	Remove emojis
17	Title Case Headings	"Strategic Negotiations And Partnerships"	"Strategic negotiations and partnerships"
18	List addiction	Everything becomes bullets	Convert to prose where appropriate
19	Unnecessary tables	3-row table that should be a sentence	Convert to prose

---

Structural Patterns (Critical)

These bypass phrase-based detection but are major tells.

Staccato Fragment Spam

Three or more consecutive short declarative sentences stating facts in parallel structure.

Before:

The model is impressive. Complex code ships fast. Documentation writes itself. Problems get solved quickly.

After:

The model is impressive — complex code ships in a single session, documentation practically writes itself, and problems that would have taken a weekend now take an afternoon.

Detection rule: 3+ consecutive sentences, all under 10 words, all declarative, parallel structure, could be bullet points.

Sentence Uniformity

Every sentence 10–15 words. Short. Punchy. Exhausting. Real writing has rhythm — mix 5-word sentences for impact with 25-word sentences that explore implications.

Comparator Sentences

Before:

This isn't theoretical. It's practical. It's not about X. It's about Y. It's not only a security add-on. It's a foundational architectural element.

After: Just state what it is.

AI loves this rhetorical pattern. It sounds punchy but wastes words telling you what something isn't. Variants: "not just X — it's Y", "not only X", "more than just X".

Over-Balanced Sections

Every section same length. All paragraphs 3–4 sentences. AI doesn't have opinions, so it gives balanced coverage to everything. Real writing reflects priorities.

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Communication Patterns

#	Pattern	Before	After
20	Chatbot artifacts	"I hope this helps! Let me know if..."	Remove entirely
21	Cutoff disclaimers	"While details are limited in available sources..."	Find sources or remove
22	Sycophantic tone	"Great question! You're absolutely right!"	Respond directly
23	Flattery sandwiches	"While traditional methods have merit, modern approaches offer..."	State your actual position

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Advanced Structural Tells

Manufactured Personality

Before:

Five services. Five tabs. Five headaches. That got old fast.

After:

I use five different services for my workflow. They're solid platforms, but like most SaaS tools, each means another dashboard, another context switch.

Self-Promotional Framing

Before:

I shipped 11 projects over the holidays. Here's what I learned.

After:

Most developers aren't aware that [observation about the reader's situation].

The author's experience is evidence, not the story.

Explanatory Header Templates

Headers that promise insight but deliver template structure:

• "Why This Actually Works"
• "What This Means For You"
• "The Real Reason..."
• "Here's What's Really Going On"

Fix: Replace with descriptive headers that summarize actual content.

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Filler and Hedging

#	Pattern	Before	After
24	Filler phrases	"In order to" / "Due to the fact that"	"To" / "Because"
25	Excessive hedging	"could potentially possibly"	"may"
26	Generic conclusions	"The future looks bright"	Specific plans or facts

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Scoring System

Pattern Type	Points
Each Tier 1 phrase	+3
Each Tier 2 phrase (repeated)	+2
Tier 3 cluster (3+ in section)	+2
Failed horoscope test	+5
Staccato fragment spam (per instance)	+4
Sentence uniformity detected	+3
Comparator sentences (per instance)	+2
Manufactured personality	+4
Self-promotional framing	+5
Template headers (per instance)	+2

Score interpretation:

• 0–5: Low risk (minor edits)
• 6–12: Medium risk (significant editing required)
• 13+: High risk (likely unedited AI output)

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Editor Mode (Default)

This skill is an editor, not a critic. After detection:

1. Apply all fixes directly using the Edit tool
2. Report changes made with before/after examples
3. Save the cleaned file in place

Fix priority:

1. Remove all Tier 1 phrases
2. Deduplicate Tier 2 phrases (keep first, vary subsequent)
3. Break up staccato fragments (combine with em-dashes, commas, conjunctions)
4. Fix comparator sentences (just state what it is)
5. Vary sentence lengths where uniformity detected

To audit without editing, user must explicitly request "audit only."

Architecture and technical documentation has different expectations than blog posts or marketing copy. In those contexts, bullet lists are not "list addiction" — they are the format. Title Case is not a style mistake if the project convention uses it. Apply pattern detection with calibration to context: flag what genuinely sounds AI-generated for the genre, not what violates blog-post norms.

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Output Format

## AntiSlop Report

**Horoscope Test:** [PASS/FAIL] — [reason]
**Slop Score:** [X] → [Y] — [Risk Level]

### Fixes Applied

| Location | Before | After |
|----------|--------|-------|
| Line 3 | "Let's delve into the details" | "Here are the details" |

### Remaining Considerations
- [Any issues requiring human judgment]

### The Core Principle
Your voice is in the specificity, the opinions, the rough edges, and the rhythm. Protect those.

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Pattern Refresh Protocol

Patterns go stale as AI models evolve. Check last-refreshed in frontmatter. If >30 days old, refresh first.

Refresh workflow:

1. Fetch latest patterns from Wikipedia:

curl -s "https://en.wikipedia.org/w/api.php?action=parse&page=Wikipedia:Signs_of_AI_writing&prop=wikitext&format=json" | python3 -c "
import json, sys
data = json.load(sys.stdin)
print(data['parse']['wikitext']['*'][:30000])
" > /tmp/antislop-signs.txt

curl -s "https://en.wikipedia.org/w/api.php?action=parse&page=Wikipedia:WikiProject_AI_Cleanup&prop=wikitext&format=json" | python3 -c "
import json, sys
data = json.load(sys.stdin)
print(data['parse']['wikitext']['*'][:30000])
" > /tmp/antislop-cleanup.txt

2. Read output and diff against patterns already in this skill
3. For genuinely new patterns not already covered: classify into Tier 1/2/3, add to appropriate table with example and fix, update pattern count
4. Update last-refreshed date in frontmatter
5. Report what was added (if anything)

Don't add duplicates — many Wikipedia patterns are already covered here under different names.

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References

• Wikipedia: Signs of AI writing
• WikiProject AI Cleanup
• Finnish study on "delve" usage (56,878 essays)
• Georgia Tech analysis (168.3M articles)

---

Core Principle

AI slop isn't about individual words — it's about patterns.

One "moreover" doesn't make content AI-generated. But "moreover" + "it's worth noting" + "delve into" + uniform sentences + emoji headers = obvious slop.

The goal is writing that sounds like a specific human with specific opinions, not a very polite committee trying not to offend anyone.