| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 21 | | adverbTagCount | 1 | | adverbTags | | 0 | "she said finally [finally]" |
| | dialogueSentences | 41 | | tagDensity | 0.512 | | leniency | 1 | | rawRatio | 0.048 | | effectiveRatio | 0.048 | |
| 85.54% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1729 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "suddenly" | | 1 | "completely" | | 2 | "very" | | 3 | "gently" |
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| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 79.76% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1729 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "absolutely" | | 1 | "weight" | | 2 | "silence" | | 3 | "pawn" | | 4 | "tinged" |
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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 | 76 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 76 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 97 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 74 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1740 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 20 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 18 | | wordCount | 1257 | | uniqueNames | 12 | | maxNameDensity | 0.24 | | worstName | "Silas" | | maxWindowNameDensity | 1 | | worstWindowName | "Silas" | | discoveredNames | | Soho | 1 | | Raven | 1 | | Nest | 2 | | Silas | 3 | | Blackwood | 1 | | Uncle | 1 | | Si | 1 | | Brendan | 2 | | Prague | 1 | | Jennifer | 1 | | Rory | 2 | | Cardiff | 2 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Silas" | | 3 | "Blackwood" | | 4 | "Uncle" | | 5 | "Si" | | 6 | "Brendan" | | 7 | "Jennifer" | | 8 | "Rory" |
| | places | | 0 | "Soho" | | 1 | "Prague" | | 2 | "Cardiff" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 53 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.575 | | wordCount | 1740 | | matches | | 0 | "no threat to anyone but" |
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| 63.57% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 3 | | totalSentences | 97 | | matches | | 0 | "learned that the" | | 1 | "was that he shouting that he" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 43 | | mean | 40.47 | | std | 34.21 | | cv | 0.845 | | sampleLengths | | 0 | 84 | | 1 | 46 | | 2 | 86 | | 3 | 24 | | 4 | 3 | | 5 | 61 | | 6 | 29 | | 7 | 23 | | 8 | 85 | | 9 | 3 | | 10 | 40 | | 11 | 159 | | 12 | 25 | | 13 | 27 | | 14 | 43 | | 15 | 5 | | 16 | 79 | | 17 | 15 | | 18 | 102 | | 19 | 20 | | 20 | 46 | | 21 | 6 | | 22 | 43 | | 23 | 57 | | 24 | 17 | | 25 | 20 | | 26 | 3 | | 27 | 6 | | 28 | 47 | | 29 | 23 | | 30 | 30 | | 31 | 54 | | 32 | 90 | | 33 | 4 | | 34 | 1 | | 35 | 13 | | 36 | 82 | | 37 | 5 | | 38 | 75 | | 39 | 30 | | 40 | 52 | | 41 | 6 | | 42 | 71 |
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| 96.03% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 76 | | matches | | 0 | "were papered" | | 1 | "gets caught" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 216 | | matches | | 0 | "wasn't turning" | | 1 | "was filing" | | 2 | "was thinking" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 9 | | semicolonCount | 1 | | flaggedSentences | 10 | | totalSentences | 97 | | ratio | 0.103 | | matches | | 0 | "The rain had been falling since four o'clock, and by midnight Soho wore it like a bad conscience — gutters running, neon smeared across the wet pavement in long bleeding streaks." | | 1 | "He heard it over the low murmur of the last two drinkers — the bell, the gust of cold, the rain suddenly loud and then suddenly shut out." | | 2 | "She stopped two steps inside the door, and before she did anything else she read the room — the front door behind her, the corridor to the lavatories, the fire exit past the phone booth, the two slumped regulars who posed no threat to anyone but their own livers." | | 3 | "He watched it move through her — the refusal to believe, the check, the second look, the surrender." | | 4 | "The walls of the Nest were papered in them — old maps, framed photographs, coastlines of a world that had mostly stopped existing." | | 5 | "When she reached for it her sleeve rode up her left wrist, and there it was — the small crescent scar, pale as a fingernail moon." | | 6 | "Up close he could see the years laid over the child like a bad transparency — the jaw was Jennifer's, the stubbornness was all Brendan, but the wariness was new, and it was hers, and he hated it on sight." | | 7 | "She looked at him then, straight on, and he watched her decide something — watched her weigh him, the way he'd taught her father to weigh a witness a lifetime ago in a different city." | | 8 | "The question caught her wrong-footed, and for one second the wariness dropped and there she was — nine years old, crowing over his king, accusing him of delaying the endgame because he couldn't bear to lose to a child." | | 9 | "Everyone carries it; the trick is finding someone who'll set it on the bar between them for a minute." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1107 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 37 | | adverbRatio | 0.03342366757000903 | | lyAdverbCount | 13 | | lyAdverbRatio | 0.011743450767841012 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 97 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 97 | | mean | 17.94 | | std | 16.39 | | cv | 0.914 | | sampleLengths | | 0 | 31 | | 1 | 53 | | 2 | 6 | | 3 | 28 | | 4 | 12 | | 5 | 4 | | 6 | 16 | | 7 | 49 | | 8 | 17 | | 9 | 9 | | 10 | 15 | | 11 | 3 | | 12 | 9 | | 13 | 18 | | 14 | 34 | | 15 | 3 | | 16 | 3 | | 17 | 4 | | 18 | 16 | | 19 | 3 | | 20 | 12 | | 21 | 11 | | 22 | 23 | | 23 | 35 | | 24 | 27 | | 25 | 3 | | 26 | 14 | | 27 | 3 | | 28 | 23 | | 29 | 50 | | 30 | 18 | | 31 | 26 | | 32 | 35 | | 33 | 3 | | 34 | 27 | | 35 | 11 | | 36 | 14 | | 37 | 7 | | 38 | 20 | | 39 | 18 | | 40 | 25 | | 41 | 5 | | 42 | 19 | | 43 | 51 | | 44 | 9 | | 45 | 3 | | 46 | 12 | | 47 | 15 | | 48 | 40 | | 49 | 22 |
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| 59.11% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 11 | | diversityRatio | 0.422680412371134 | | totalSentences | 97 | | uniqueOpeners | 41 | |
| 53.76% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 62 | | matches | | 0 | "Then the face arrived under" |
| | ratio | 0.016 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 36 | | totalSentences | 62 | | matches | | 0 | "He heard it over the" | | 1 | "He looked up the way" | | 2 | "She stopped two steps inside" | | 3 | "She took the measure of" | | 4 | "She stopped as if she'd" | | 5 | "He watched it move through" | | 6 | "He was privately glad." | | 7 | "He'd never earned the title" | | 8 | "He set the glass down" | | 9 | "She glanced at them as" | | 10 | "He limped out from behind" | | 11 | "He put the towel in" | | 12 | "She dried her hands, wrapped" | | 13 | "He had carried her into" | | 14 | "She was seven." | | 15 | "She'd been trying to rescue" | | 16 | "She drank the whiskey the" | | 17 | "He filed that away with" | | 18 | "she said, into the glass" | | 19 | "He came around the bar" |
| | ratio | 0.581 | |
| 56.77% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 50 | | totalSentences | 62 | | matches | | 0 | "The rain had been falling" | | 1 | "The green sign above The" | | 2 | "The door opened at eleven" | | 3 | "He heard it over the" | | 4 | "He looked up the way" | | 5 | "A woman came in." | | 6 | "She stopped two steps inside" | | 7 | "She took the measure of" | | 8 | "Silas recognized the habit before" | | 9 | "She stopped as if she'd" | | 10 | "He watched it move through" | | 11 | "The last time he had" | | 12 | "He was privately glad." | | 13 | "He'd never earned the title" | | 14 | "He set the glass down" | | 15 | "The walls of the Nest" | | 16 | "She glanced at them as" | | 17 | "He limped out from behind" | | 18 | "He put the towel in" | | 19 | "She dried her hands, wrapped" |
| | ratio | 0.806 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 62 | | matches | | 0 | "Because a man who has" | | 1 | "Because after Prague there had" |
| | ratio | 0.032 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 37 | | technicalSentenceCount | 9 | | matches | | 0 | "The green sign above The Raven's Nest buzzed its one broken letter, and Silas Blackwood stood behind his bar polishing a glass that was already clean, mostly be…" | | 1 | "She stopped two steps inside the door, and before she did anything else she read the room — the front door behind her, the corridor to the lavatories, the fire …" | | 2 | "The walls of the Nest were papered in them — old maps, framed photographs, coastlines of a world that had mostly stopped existing." | | 3 | "He put the towel in front of her and poured two fingers of whiskey without asking, because the girl he remembered had taken her ginger beer seriously and the wo…" | | 4 | "She'd been trying to rescue a shuttlecock from the neighbor's garden and had misjudged the top of the wall in the way of seven-year-olds, which was completely." | | 5 | "Because a man who has spent his professional life writing things that could kill people gets strange about paper." | | 6 | "The question caught her wrong-footed, and for one second the wariness dropped and there she was — nine years old, crowing over his king, accusing him of delayin…" | | 7 | "Everyone carries it; the trick is finding someone who'll set it on the bar between them for a minute." | | 8 | "He got up, and his knee objected, and he led her toward the back through the green-tinged lamplight, past the maps of a world that had ended and the photographs…" |
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| 77.38% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 21 | | uselessAdditionCount | 2 | | matches | | 0 | "He came around, knee complaining the whole way" | | 1 | "She shrugged, and the shrug had a hitch in it, the left shoulder going up a fraction slower than the right" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 13 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 41 | | tagDensity | 0.317 | | leniency | 0.634 | | rawRatio | 0.077 | | effectiveRatio | 0.049 | |