aplaceforallmystuff/the-antislop/antislop

The AntiSlop

A comprehensive AI writing pattern detector and fixer. Combines patterns from Wikipedia's Signs of AI Writing with advanced structural detection and an editor mode that actually fixes problems.

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

Usage

/antislop
 
[paste your text here]

Or ask Claude to check text directly:

Please run antislop on this: [your text]

How It Works

1. Run the Horoscope Test - Could anyone have written this for anyone?
2. Scan for patterns - 50+ known AI tells across 6 categories, structure weighted above vocabulary
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

Detection Patterns (50+, structure-weighted)

Tier 1: AI-vocabulary density (weight the cluster, not the word)

These words were near-certain AI tells in the 2023–2024 GPT-3.5/4 era. Frontier models in 2025–2026 emit the loudest of them far less, so a single hit now means little — treat this as a density probe, not a blocklist. Three or more clustered in a passage is still a reliable tell; one "leverage" in isolation usually is not. Score the density (see Scoring), not each word.

Legacy signals — weakened, still worth flagging in clusters:

Current signals — the vocabulary today's models still lean on:

Research evidence (lexical tells peaked 2023–2024; density-based detection ages better than any word list):

• 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
• 2025–2026 shift: frontier models were tuned against the loudest 2023 tells, so detection now leans on structure (below), where the signal has held.

Tier 2: Suspicious When Repeated

Problematic when overused or clustered.

Tier 3: Watch for Clusters

Fine individually, problematic together.

Content Patterns

Fabricated precision is a current-model tell: a suspiciously exact figure (47%, 3.2x, "over 10,000 hours") presented without a citation, to manufacture authority. Flag any hard statistic that has no source attached.

Language Patterns

Style Patterns

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. AI's version of bullets pretending to be prose.

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 that are all under 10 words, all declarative, following parallel structure, and 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.

This isn't a feature. It's a philosophy.

It's not about X. It's about Y.

After:

Here's how it works in practice:

[Just state what it is]

AI loves this rhetorical pattern. It sounds punchy but wastes words telling you what something isn't.

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.

Communication Patterns

Advanced Structural Tells

Manufactured Personality

AI trying to sound human but coming across as performative:

Before:

Five services. Five tabs. Five headaches.

That got old fast.

So I built an MCP server that unifies all of them.

After:

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

No manufactured punch. No snark. Just describes the situation.

Self-Promotional Framing

Content positioning author's accomplishments as the headline instead of reader's transformation.

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]. Here's what's changing...

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"