@athola/slop-detector

---
name: slop-detector
description: Detect and flag AI-generated content markers in documentation and prose.
  Use when reviewing documentation for AI markers, cleaning up LLM-generated content,
  or auditing prose quality. Do not use when generating new content (use doc-generator)
  or learning writing styles (use style-learner).
category: writing-quality
tags:
- ai-detection
- slop
- writing
- cleanup
- documentation
- quality
tools:
- Read
- Grep
- TodoWrite
complexity: medium
estimated_tokens: 4200
progressive_loading: true
modules:
- vocabulary-patterns
- structural-patterns
- fiction-patterns
- remediation-strategies
- language-support
- config-file
- progress-indicators
- ci-integration
- metrics
- i18n-patterns
dependencies:
- scribe:shared
---

# AI Slop Detection

AI slop is identified by patterns of usage rather than individual words. While a single "delve" might be acceptable, its proximity to markers like "tapestry" or "embark" signals generated text. We analyze the density of these markers per 100 words, their clustering, and whether the overall tone fits the document type.

## Execution Workflow

Start by identifying target files and classifying them as technical docs, narrative prose, or code comments. This allows for context-aware scoring during analysis.

### Language Detection

- Auto-detect language from text content using function word frequency
- Override with explicit `--lang` parameter (en, de, fr, es)
- Load language-specific patterns from `data/languages/{lang}.yaml`
- Fall back to English if detection confidence is low
- See `modules/language-support.md` for details on cultural calibration

### Vocabulary and Phrase Detection

Load: `@modules/vocabulary-patterns.md`

We categorize markers into three tiers based on confidence. Tier 1 words appear dramatically more often in AI text and include "delve," "multifaceted," and "leverage." Tier 2 covers context-dependent transitions like "moreover" or "subsequently," while Tier 3 identifies vapid phrases such as "In today's fast-paced world" or "cannot be overstated."

| Word | Context | Human Alternative |
|------|---------|-------------------|
| delve | "delve into" | explore, examine, look at |
| tapestry | "rich tapestry" | mix, combination, variety |
| realm | "in the realm of" | in, within, regarding |
| embark | "embark on a journey" | start, begin |
| beacon | "a beacon of" | example, model |
| spearheaded | formal attribution | led, started |
| multifaceted | describing complexity | complex, varied |
| comprehensive | describing scope | thorough, complete |
| pivotal | importance marker | key, important |
| nuanced | sophistication signal | subtle, detailed |
| meticulous/meticulously | care marker | careful, detailed |
| intricate | complexity marker | detailed, complex |
| showcasing | display verb | showing, displaying |
| leveraging | business jargon | using |
| streamline | optimization verb | simplify, improve |

### Tier 2: Medium-Confidence Markers (Score: 2 each)

Common but context-dependent:

| Category | Words |
|----------|-------|
| Transition overuse | moreover, furthermore, indeed, notably, subsequently |
| Intensity clustering | significantly, substantially, fundamentally, profoundly |
| Hedging stacks | potentially, typically, often, might, perhaps |
| Action inflation | revolutionize, transform, unlock, unleash, elevate |
| Empty emphasis | crucial, vital, essential, paramount |

### Tier 3: Phrase Patterns (Score: 2-4 each)

| Phrase | Score | Issue |
|--------|-------|-------|
| "In today's fast-paced world" | 4 | Vapid opener |
| "It's worth noting that" | 3 | Filler |
| "At its core" | 2 | Positional crutch |
| "Cannot be overstated" | 3 | Empty emphasis |
| "A testament to" | 3 | Attribution cliche |
| "Navigate the complexities" | 4 | Business speak |
| "Unlock the potential" | 4 | Marketing speak |
| "Treasure trove of" | 3 | Overused metaphor |
| "Game changer" | 3 | Buzzword |
| "Look no further" | 4 | Sales pitch |
| "Nestled in the heart of" | 4 | Travel writing cliche |
| "Embark on a journey" | 4 | Melodrama |
| "Ever-evolving landscape" | 4 | Tech cliche |
| "Hustle and bustle" | 3 | Filler |

## Step 3: Structural Pattern Detection

Load: `@modules/structural-patterns.md`

### Em Dash Overuse

Count em dashes (—) per 1000 words:
- **0-2**: Normal human range
- **3-5**: Elevated, review usage
- **6+**: Strong AI signal

```bash
# Count em dashes in file
grep -o '—' file.md | wc -l
```

### Tricolon Detection

AI loves groups of three with alliteration:
- "fast, efficient, and reliable"
- "clear, concise, and compelling"
- "robust, reliable, and resilient"

Pattern: `adjective, adjective, and adjective` with similar sounds.

### List-to-Prose Ratio

Count bullet points vs paragraph sentences:
- **>60% bullets**: AI tendency
- **Emoji-led bullets**: Strong AI signal in technical docs

### Sentence Length Uniformity

Measure standard deviation of sentence lengths:
- **Low variance** (SD < 5 words): AI monotony
- **High variance** (SD > 10 words): Human variation

### Paragraph Symmetry

AI produces "blocky" text with uniform paragraph lengths. Check if paragraphs cluster around the same word count.

## Step 4: Sycophantic Pattern Detection

Especially relevant for conversational or instructional content:

| Phrase | Issue |
|--------|-------|
| "I'd be happy to" | Servile opener |
| "Great question!" | Empty validation |
| "Absolutely!" | Over-agreement |
| "That's a wonderful point" | Flattery |
| "I'm glad you asked" | Filler |
| "You're absolutely right" | Sycophancy |

These phrases add no information and signal generated content.

## Step 5: Calculate Slop Density Score

```
slop_score = (tier1_count * 3 + tier2_count * 2 + phrase_count * avg_phrase_score) / word_count * 100
```

| Score | Rating | Action |
|-------|--------|--------|
| 0-1.0 | Clean | No action needed |
| 1.0-2.5 | Light | Spot remediation |
| 2.5-5.0 | Moderate | Section rewrite recommended |
| 5.0+ | Heavy | Full document review |

## Step 6: Generate Report

Output format:

```markdown
## Slop Detection Report: [filename]

**Overall Score**: X.X / 10 (Rating)
**Word Count**: N words
**Markers Found**: N total

### High-Confidence Markers
- Line 23: "delve into" -> consider: "explore"
- Line 45: "rich tapestry" -> consider: "variety"

### Structural Issues
- Em dash density: 8/1000 words (HIGH)
- Bullet ratio: 72% (ELEVATED)
- Sentence length SD: 3.2 words (LOW VARIANCE)

### Phrase Patterns
- Line 12: "In today's fast-paced world" (vapid opener)
- Line 89: "cannot be overstated" (empty emphasis)

### Recommendations
1. Replace [specific word] with [alternative]
2. Convert bullet list at line 34-56 to prose
3. Vary sentence structure in paragraphs 3-5
```

## Module Reference

- See `modules/fiction-patterns.md` for narrative-specific slop markers
- See `modules/remediation-strategies.md` for fix recommendations

## Integration with Remediation

After detection, invoke `Skill(scribe:doc-generator)` with `--remediate` flag to apply fixes, or manually edit using the report as a guide.

## Exit Criteria

- All target files scanned
- Density scores calculated
- Report generated with actionable recommendations
- High-severity items flagged for immediate attention