| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 6 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 18 | | tagDensity | 0.333 | | leniency | 0.667 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 90.85% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1093 | | totalAiIsmAdverbs | 2 | | found | | | highlights | | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 86.28% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1093 | | totalAiIsms | 3 | | found | | | highlights | | 0 | "calculating" | | 1 | "structure" | | 2 | "weight" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 0 | | maxInWindow | 0 | | found | (empty) | | highlights | (empty) | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 67 | | matches | (empty) | |
| 78.89% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 67 | | filterMatches | | | hedgeMatches | | 0 | "started to" | | 1 | "managed to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 78 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 65 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 9 | | totalWords | 1096 | | ratio | 0.008 | | matches | | 0 | "leave what you are above ground or leave entirely." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 29 | | wordCount | 936 | | uniqueNames | 14 | | maxNameDensity | 0.75 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Quinn" | | discoveredNames | | Wardour | 1 | | Street | 2 | | Raven | 1 | | Nest | 1 | | Saint | 2 | | Christopher | 2 | | Camden | 2 | | Static | 1 | | High | 1 | | Morris | 2 | | Herrera | 5 | | Andalusian | 1 | | London | 1 | | Quinn | 7 |
| | persons | | 0 | "Saint" | | 1 | "Christopher" | | 2 | "Morris" | | 3 | "Herrera" | | 4 | "Andalusian" | | 5 | "Quinn" |
| | places | | 0 | "Wardour" | | 1 | "Street" | | 2 | "Raven" | | 3 | "Camden" | | 4 | "High" | | 5 | "London" |
| | globalScore | 1 | | windowScore | 1 | |
| 0.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 46 | | glossingSentenceCount | 4 | | matches | | 0 | "looked like a derelict service structure" | | 1 | "looked like that — and disappeared inside" | | 2 | "something between woodsmoke and petrichor and b" | | 3 | "quite pity and wasn't quite a warning, and she put the torch back on her belt and took the bone token off the shelf" | | 4 | "quite a warning, and she put the torch back on her belt and took the bone token off the shelf" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1096 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 78 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 40 | | mean | 27.4 | | std | 22.05 | | cv | 0.805 | | sampleLengths | | 0 | 43 | | 1 | 7 | | 2 | 77 | | 3 | 9 | | 4 | 33 | | 5 | 55 | | 6 | 13 | | 7 | 41 | | 8 | 12 | | 9 | 10 | | 10 | 3 | | 11 | 57 | | 12 | 13 | | 13 | 70 | | 14 | 8 | | 15 | 28 | | 16 | 5 | | 17 | 38 | | 18 | 42 | | 19 | 4 | | 20 | 72 | | 21 | 5 | | 22 | 16 | | 23 | 19 | | 24 | 28 | | 25 | 43 | | 26 | 5 | | 27 | 15 | | 28 | 47 | | 29 | 54 | | 30 | 12 | | 31 | 21 | | 32 | 17 | | 33 | 30 | | 34 | 16 | | 35 | 4 | | 36 | 4 | | 37 | 74 | | 38 | 7 | | 39 | 39 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 67 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 163 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 11 | | semicolonCount | 1 | | flaggedSentences | 8 | | totalSentences | 78 | | ratio | 0.103 | | matches | | 0 | "She'd seen him before — twice — at two separate scenes she couldn't explain." | | 1 | "He glanced back once, just enough for her to catch his face — wide-eyed, jaw set — and then he cut left down a narrow passage between a boarded-up restaurant and a laundrette." | | 2 | "Herrera was picking his way across it towards what looked like a derelict service structure — a concrete box with a rusted steel door, the kind of utility housing the city had forgotten about for forty years." | | 3 | "He reached the steel door, wrenched it open — it moved far too easily for a door that looked like that — and disappeared inside." | | 4 | "Eight minutes for backup to reach where she'd been; they'd have no idea she was here." | | 5 | "A smell came up from below — something she couldn't name immediately, something between woodsmoke and petrichor and burnt copper, layered over the cold mineral reek of deep underground air." | | 6 | "The torch beam caught movement below — Herrera, stopped at the bottom, looking up at her." | | 7 | "The steel door stood open above her, rain-sound fading with each step until all she could hear was the concrete taking her weight and the distant, low murmur of what sounded — impossibly — like a crowd." |
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| 91.41% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 931 | | adjectiveStacks | 1 | | stackExamples | | 0 | "yellow under light she" |
| | adverbCount | 40 | | adverbRatio | 0.04296455424274973 | | lyAdverbCount | 13 | | lyAdverbRatio | 0.013963480128893663 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 78 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 78 | | mean | 14.05 | | std | 11.72 | | cv | 0.834 | | sampleLengths | | 0 | 24 | | 1 | 19 | | 2 | 3 | | 3 | 4 | | 4 | 28 | | 5 | 14 | | 6 | 14 | | 7 | 21 | | 8 | 7 | | 9 | 2 | | 10 | 33 | | 11 | 10 | | 12 | 17 | | 13 | 28 | | 14 | 13 | | 15 | 7 | | 16 | 34 | | 17 | 5 | | 18 | 7 | | 19 | 2 | | 20 | 8 | | 21 | 3 | | 22 | 15 | | 23 | 25 | | 24 | 17 | | 25 | 13 | | 26 | 15 | | 27 | 18 | | 28 | 37 | | 29 | 3 | | 30 | 5 | | 31 | 3 | | 32 | 25 | | 33 | 5 | | 34 | 6 | | 35 | 16 | | 36 | 6 | | 37 | 10 | | 38 | 1 | | 39 | 5 | | 40 | 30 | | 41 | 4 | | 42 | 2 | | 43 | 4 | | 44 | 39 | | 45 | 33 | | 46 | 5 | | 47 | 16 | | 48 | 12 | | 49 | 7 |
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| 60.68% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.41025641025641024 | | totalSentences | 78 | | uniqueOpeners | 32 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 63 | | matches | | 0 | "Then he turned off the" | | 1 | "Then she looked at Herrera," |
| | ratio | 0.032 | |
| 29.52% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 30 | | totalSentences | 63 | | matches | | 0 | "He was fast." | | 1 | "She'd give him that." | | 2 | "She'd spotted him outside the" | | 3 | "She'd seen him before —" | | 4 | "Her voice cracked against the" | | 5 | "He glanced back once, just" | | 6 | "Her left foot punched through" | | 7 | "She emerged onto a wider" | | 8 | "She pressed the radio on" | | 9 | "she checked the street sign" | | 10 | "She pushed harder." | | 11 | "He was fast but she" | | 12 | "She watched him tire in" | | 13 | "He knew it too, because" | | 14 | "She called again." | | 15 | "He didn't answer." | | 16 | "He reached the steel door," | | 17 | "She hadn't radioed her new" | | 18 | "Her torch was on her" | | 19 | "She drew it and swept" |
| | ratio | 0.476 | |
| 47.30% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 52 | | totalSentences | 63 | | matches | | 0 | "The rain came sideways down" | | 1 | "Quinn ran, her boots hammering" | | 2 | "He was fast." | | 3 | "She'd give him that." | | 4 | "She'd spotted him outside the" | | 5 | "She'd seen him before —" | | 6 | "The same man, the same" | | 7 | "Her voice cracked against the" | | 8 | "He glanced back once, just" | | 9 | "Quinn followed, her shoulder clipping" | | 10 | "The passage was barely wide" | | 11 | "Her left foot punched through" | | 12 | "She emerged onto a wider" | | 13 | "She pressed the radio on" | | 14 | "she checked the street sign" | | 15 | "Static, then a woman's voice." | | 16 | "Herrera would be long gone" | | 17 | "She pushed harder." | | 18 | "He was fast but she" | | 19 | "She watched him tire in" |
| | ratio | 0.825 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 63 | | matches | (empty) | | ratio | 0 | |
| 81.63% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 35 | | technicalSentenceCount | 3 | | matches | | 0 | "When she'd stepped towards him he'd bolted without a word, which told her everything she needed to know about his conscience." | | 1 | "Three years ago Morris had followed something she didn't understand through a door she hadn't been able to explain, and they'd found him two days later in a way…" | | 2 | "A bone token sat on a wooden shelf built into the wall at shoulder height, and below it, scratched into the tile in letters she shouldn't have been able to read…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 6 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |