| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 5 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 13 | | tagDensity | 0.385 | | leniency | 0.769 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1287 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 84.46% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1287 | | totalAiIsms | 4 | | found | | | highlights | | 0 | "predictable" | | 1 | "footfall" | | 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 | 91 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 91 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 99 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 54 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 1 | | totalWords | 1296 | | ratio | 0.001 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 39 | | wordCount | 1225 | | uniqueNames | 17 | | maxNameDensity | 0.98 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Quinn" | | discoveredNames | | Camden | 1 | | Raven | 1 | | Nest | 1 | | Tomás | 1 | | Herrera | 7 | | Tube | 1 | | Kentish | 2 | | Town | 2 | | Road | 1 | | Quinn | 12 | | Morris | 2 | | Deptford | 1 | | Save | 1 | | Twelve | 1 | | Victorian | 1 | | Seville | 1 | | Left | 3 |
| | persons | | 0 | "Nest" | | 1 | "Tomás" | | 2 | "Herrera" | | 3 | "Quinn" | | 4 | "Morris" | | 5 | "Left" |
| | places | | 0 | "Raven" | | 1 | "Tube" | | 2 | "Kentish" | | 3 | "Town" | | 4 | "Road" | | 5 | "Deptford" | | 6 | "Seville" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 57 | | glossingSentenceCount | 1 | | matches | | 0 | "sounded like — a long soft grinding, like" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.772 | | wordCount | 1296 | | matches | | 0 | "not the black of a derelict stairwell but a warm crawling amber, like firelight, going down" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 99 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 40 | | mean | 32.4 | | std | 22.51 | | cv | 0.695 | | sampleLengths | | 0 | 60 | | 1 | 19 | | 2 | 35 | | 3 | 5 | | 4 | 83 | | 5 | 50 | | 6 | 18 | | 7 | 69 | | 8 | 8 | | 9 | 2 | | 10 | 50 | | 11 | 3 | | 12 | 38 | | 13 | 19 | | 14 | 83 | | 15 | 39 | | 16 | 45 | | 17 | 41 | | 18 | 13 | | 19 | 70 | | 20 | 19 | | 21 | 42 | | 22 | 50 | | 23 | 19 | | 24 | 3 | | 25 | 6 | | 26 | 3 | | 27 | 54 | | 28 | 35 | | 29 | 30 | | 30 | 16 | | 31 | 57 | | 32 | 25 | | 33 | 28 | | 34 | 37 | | 35 | 7 | | 36 | 30 | | 37 | 23 | | 38 | 6 | | 39 | 56 |
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| 82.13% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 6 | | totalSentences | 91 | | matches | | 0 | "been taught" | | 1 | "been taught" | | 2 | "been given" | | 3 | "been prised" | | 4 | "was supposed" | | 5 | "was frightened " | | 6 | "was winded" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 201 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 9 | | semicolonCount | 1 | | flaggedSentences | 7 | | totalSentences | 99 | | ratio | 0.071 | | matches | | 0 | "He turned it over in his fingers like a man counting rosary beads, and the streetlight caught it — not plastic, not metal." | | 1 | "Water sheeted off a broken gutter and she went through it without slowing, and maybe that was the mistake — the splash, the sound of a footfall that wasn't rain — because Herrera's head came round and this time he didn't just look." | | 2 | "He hit it at speed, hauled himself up two rungs, then dropped back down and cut right instead — a feint, and a good one; she'd already committed her weight towards the ladder and lost a full second recovering." | | 3 | "He was breathing hard, one hand flat against the door, and he was frightened — but not of her." | | 4 | "\"I am telling you.\" He pressed the pale disc against a plate beside the handle and Quinn heard something in the door move that no lock in her experience had ever sounded like — a long soft grinding, like teeth." | | 5 | "Somewhere under her feet, faint through brick and clay, something was playing music — a thin reeded thing with too many notes in it." | | 6 | "She turned her radio off before she went in — because a signal was a leash and a leash could be pulled — and then she stepped through onto the top of a staircase that smelled of tallow and cardamom, and the door shut behind her, and the amber light went down and down and down." |
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| 92.83% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 498 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 24 | | adverbRatio | 0.04819277108433735 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.004016064257028112 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 99 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 99 | | mean | 13.09 | | std | 12.18 | | cv | 0.931 | | sampleLengths | | 0 | 11 | | 1 | 32 | | 2 | 14 | | 3 | 3 | | 4 | 19 | | 5 | 3 | | 6 | 24 | | 7 | 8 | | 8 | 5 | | 9 | 39 | | 10 | 21 | | 11 | 8 | | 12 | 1 | | 13 | 14 | | 14 | 20 | | 15 | 1 | | 16 | 1 | | 17 | 23 | | 18 | 1 | | 19 | 4 | | 20 | 18 | | 21 | 49 | | 22 | 3 | | 23 | 3 | | 24 | 14 | | 25 | 8 | | 26 | 2 | | 27 | 5 | | 28 | 2 | | 29 | 43 | | 30 | 3 | | 31 | 8 | | 32 | 27 | | 33 | 3 | | 34 | 16 | | 35 | 3 | | 36 | 3 | | 37 | 22 | | 38 | 32 | | 39 | 5 | | 40 | 21 | | 41 | 8 | | 42 | 17 | | 43 | 14 | | 44 | 6 | | 45 | 39 | | 46 | 20 | | 47 | 14 | | 48 | 7 | | 49 | 13 |
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| 75.08% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.5050505050505051 | | totalSentences | 99 | | uniqueOpeners | 50 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 79 | | matches | | 0 | "Then the side door opened" | | 1 | "Then he ran." | | 2 | "Somewhere under her feet, faint" | | 3 | "Then she stood, wiped the" |
| | ratio | 0.051 | |
| 78.23% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 28 | | totalSentences | 79 | | matches | | 0 | "She didn't move." | | 1 | "She stayed on the far" | | 2 | "He checked behind him at" | | 3 | "She timed her steps to" | | 4 | "He turned it over in" | | 5 | "She'd filed it." | | 6 | "She'd asked questions." | | 7 | "She'd been given a bereavement" | | 8 | "She closed to thirty metres." | | 9 | "He saw her." | | 10 | "He was quick." | | 11 | "He went off the pavement" | | 12 | "Her lungs began their protest" | | 13 | "His answer was a fire" | | 14 | "He hit it at speed," | | 15 | "She knew this place." | | 16 | "Her hand went to her" | | 17 | "He was breathing hard, one" | | 18 | "He kept glancing past her," | | 19 | "His accent thickened when he" |
| | ratio | 0.354 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 55 | | totalSentences | 79 | | matches | | 0 | "The rain came down like" | | 1 | "Quinn had been standing in" | | 2 | "Water ran off the back" | | 3 | "She didn't move." | | 4 | "Quinn pushed off the wall." | | 5 | "She stayed on the far" | | 6 | "Herrera moved like a man" | | 7 | "He checked behind him at" | | 8 | "She timed her steps to" | | 9 | "He turned it over in" | | 10 | "She'd filed it." | | 11 | "She'd asked questions." | | 12 | "She'd been given a bereavement" | | 13 | "Herrera pocketed the token and" | | 14 | "She closed to thirty metres." | | 15 | "Water sheeted off a broken" | | 16 | "He saw her." | | 17 | "Quinn shouted, and hated herself" | | 18 | "He was quick." | | 19 | "He went off the pavement" |
| | ratio | 0.696 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 79 | | matches | (empty) | | ratio | 0 | |
| 74.83% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 42 | | technicalSentenceCount | 4 | | matches | | 0 | "Quinn had been standing in it for forty minutes outside the Raven's Nest, watching that green neon bleed across the wet pavement, and her coat had given up some…" | | 1 | "She stayed on the far side of the road for the first three hundred metres, keeping a van and then a skip between them, her boots finding the quiet parts of the …" | | 2 | "Paramedic quick, the kind of fitness that came from years of carrying dead weight up narrow stairs, and he knew the ground." | | 3 | "Her lungs began their protest at the second corner and she told them what she always told them, which was later." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 5 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 2 | | fancyTags | | 0 | "Quinn shouted (shout)" | | 1 | "He pressed (press)" |
| | dialogueSentences | 13 | | tagDensity | 0.231 | | leniency | 0.462 | | rawRatio | 0.667 | | effectiveRatio | 0.308 | |