| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 17 | | adverbTagCount | 1 | | adverbTags | | 0 | "Quinn said quietly [quietly]" |
| | dialogueSentences | 42 | | tagDensity | 0.405 | | leniency | 0.81 | | rawRatio | 0.059 | | effectiveRatio | 0.048 | |
| 86.64% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1123 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "sharply" | | 1 | "slowly" | | 2 | "slightly" |
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| 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) | |
| 19.86% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1123 | | totalAiIsms | 18 | | found | | | highlights | | 0 | "chill" | | 1 | "pulsed" | | 2 | "glinting" | | 3 | "echoed" | | 4 | "tension" | | 5 | "flickered" | | 6 | "stomach" | | 7 | "silence" | | 8 | "fractured" | | 9 | "shattered" | | 10 | "scanning" | | 11 | "uncanny" | | 12 | "pulse" | | 13 | "quickened" | | 14 | "anticipation" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "stomach dropped/sank" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 102 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 102 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 126 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 33 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1136 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 16 | | unquotedAttributions | 0 | | matches | (empty) | |
| 16.34% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 62 | | wordCount | 823 | | uniqueNames | 21 | | maxNameDensity | 2.67 | | worstName | "Quinn" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Quinn" | | discoveredNames | | Tube | 1 | | Harlow | 1 | | Quinn | 22 | | Camden | 2 | | Morris | 1 | | Kowalski | 1 | | Aurora | 1 | | Eva | 17 | | British | 1 | | Museum | 1 | | Ovaltine | 1 | | English | 1 | | Latin | 1 | | Veil | 2 | | Market | 1 | | London | 1 | | Town | 1 | | Hargrove | 1 | | Kale | 3 | | Compass | 1 | | Victor | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Morris" | | 3 | "Kowalski" | | 4 | "Eva" | | 5 | "Museum" | | 6 | "Market" | | 7 | "Hargrove" | | 8 | "Kale" | | 9 | "Victor" |
| | places | | 0 | "Camden" | | 1 | "Aurora" | | 2 | "British" | | 3 | "London" | | 4 | "Town" |
| | globalScore | 0.163 | | windowScore | 0.167 | |
| 57.41% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 54 | | glossingSentenceCount | 2 | | matches | | 0 | "looked like it had been pressed in with a" | | 1 | "looked like twisted vines forming a sigil" |
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| 23.94% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.761 | | wordCount | 1136 | | matches | | 0 | "not toward the tracks, not toward the platform’s edge, but toward the center of the platform itself" | | 1 | "not toward the platform’s edge, but toward the center of the platform itself" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 126 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 56 | | mean | 20.29 | | std | 19.91 | | cv | 0.982 | | sampleLengths | | 0 | 95 | | 1 | 24 | | 2 | 65 | | 3 | 7 | | 4 | 80 | | 5 | 12 | | 6 | 25 | | 7 | 7 | | 8 | 19 | | 9 | 70 | | 10 | 23 | | 11 | 8 | | 12 | 32 | | 13 | 15 | | 14 | 31 | | 15 | 7 | | 16 | 21 | | 17 | 8 | | 18 | 21 | | 19 | 9 | | 20 | 3 | | 21 | 37 | | 22 | 46 | | 23 | 32 | | 24 | 8 | | 25 | 30 | | 26 | 6 | | 27 | 23 | | 28 | 33 | | 29 | 19 | | 30 | 11 | | 31 | 14 | | 32 | 16 | | 33 | 36 | | 34 | 6 | | 35 | 24 | | 36 | 8 | | 37 | 11 | | 38 | 12 | | 39 | 28 | | 40 | 3 | | 41 | 2 | | 42 | 17 | | 43 | 52 | | 44 | 4 | | 45 | 3 | | 46 | 2 | | 47 | 2 | | 48 | 16 | | 49 | 6 |
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| 94.94% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 102 | | matches | | 0 | "been sealed" | | 1 | "was bathed" | | 2 | "been pressed" |
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| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 5 | | totalVerbs | 143 | | matches | | 0 | "was reciting" | | 1 | "was wearing " | | 2 | "wasn’t looking" | | 3 | "was looking" | | 4 | "were moving" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 11 | | semicolonCount | 0 | | flaggedSentences | 11 | | totalSentences | 126 | | ratio | 0.087 | | matches | | 0 | "She hadn’t expected a call like this — not here." | | 1 | "Only now, Eva wasn’t a schoolgirl — she was a researcher, her satchel bulging with books she’d probably pulled from the British Museum’s restricted archives." | | 2 | "Not even in the air — which, given the violence of the death, should have reeked of copper and fear." | | 3 | "There, in the grout between two tiles, was a mark — a symbol scratched into the cement." | | 4 | "It looked like twisted vines forming a sigil — one she’d seen in Eva’s old research notes." | | 5 | "The Veil Market moved beneath London, but only once a month — on the full moon." | | 6 | "Not with electricity — with something older." | | 7 | "“DI Hargrove? It’s Quinn. I need you to check something.” She gave the address — a disused platform beneath Camden Town." | | 8 | "Like the one Kale was wearing — tailored wool, slightly damp, as if he’d walked through fog." | | 9 | "She tapped the face — the needle spun wildly, then steadied, pointing not toward the tracks, not toward the platform’s edge, but toward the center of the platform itself." | | 10 | "His eyes flew open — black." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 668 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 16 | | adverbRatio | 0.023952095808383235 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.01347305389221557 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 126 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 126 | | mean | 9.02 | | std | 7.27 | | cv | 0.807 | | sampleLengths | | 0 | 23 | | 1 | 20 | | 2 | 24 | | 3 | 28 | | 4 | 10 | | 5 | 14 | | 6 | 12 | | 7 | 9 | | 8 | 19 | | 9 | 20 | | 10 | 5 | | 11 | 7 | | 12 | 3 | | 13 | 4 | | 14 | 15 | | 15 | 33 | | 16 | 25 | | 17 | 5 | | 18 | 7 | | 19 | 11 | | 20 | 14 | | 21 | 2 | | 22 | 5 | | 23 | 17 | | 24 | 2 | | 25 | 12 | | 26 | 28 | | 27 | 2 | | 28 | 8 | | 29 | 20 | | 30 | 13 | | 31 | 10 | | 32 | 8 | | 33 | 6 | | 34 | 14 | | 35 | 12 | | 36 | 6 | | 37 | 9 | | 38 | 8 | | 39 | 23 | | 40 | 3 | | 41 | 4 | | 42 | 7 | | 43 | 2 | | 44 | 3 | | 45 | 3 | | 46 | 3 | | 47 | 3 | | 48 | 5 | | 49 | 3 |
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| 50.26% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.3492063492063492 | | totalSentences | 126 | | uniqueOpeners | 44 | |
| 40.65% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 82 | | matches | | 0 | "Only now, Eva wasn’t a" |
| | ratio | 0.012 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 17 | | totalSentences | 82 | | matches | | 0 | "She hadn’t expected a call" | | 1 | "Her boots made little sound" | | 2 | "She didn’t need to." | | 3 | "She crouched beside the body," | | 4 | "She snapped them on, the" | | 5 | "She pointed to the victim’s" | | 6 | "It looked like it had" | | 7 | "It looked like twisted vines" | | 8 | "she said, voice tight" | | 9 | "She knelt beside Quinn, adjusting" | | 10 | "She stood again, scanning the" | | 11 | "She gave the address —" | | 12 | "She hung up, turning to" | | 13 | "She tapped the face —" | | 14 | "His body twitched." | | 15 | "His eyes flew open —" | | 16 | "She was looking at the" |
| | ratio | 0.207 | |
| 75.85% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 63 | | totalSentences | 82 | | matches | | 0 | "The Tube station had been" | | 1 | "The air smelled of rust" | | 2 | "Detective Harlow Quinn adjusted the" | | 3 | "The scene was bathed in" | | 4 | "She hadn’t expected a call" | | 5 | "Detective Quinn moved forward, her" | | 6 | "Her boots made little sound" | | 7 | "A body lay sprawled near" | | 8 | "DS Morris’s voice echoed in" | | 9 | "a voice said behind her" | | 10 | "Quinn didn’t turn." | | 11 | "She didn’t need to." | | 12 | "The tone was light, almost" | | 13 | "Eva Kowalski stood a few" | | 14 | "Quinn said, voice low" | | 15 | "Eva said, stepping forward, her" | | 16 | "Eva’s green eyes flickered toward" | | 17 | "Quinn said, reading from a" | | 18 | "She crouched beside the body," | | 19 | "Quinn reached into her coat" |
| | ratio | 0.768 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 82 | | matches | (empty) | | ratio | 0 | |
| 87.91% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 26 | | technicalSentenceCount | 2 | | matches | | 0 | "The scene was bathed in the sickly yellow glow of crime scene lamps, their cables snaking through puddles of water that had pooled on the cracked concrete floor…" | | 1 | "She knelt beside Quinn, adjusting her glasses, then recoiled as if burned." |
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| 66.18% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 17 | | uselessAdditionCount | 2 | | matches | | 0 | "Quinn said, voice low" | | 1 | "she said, voice tight" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 12 | | fancyCount | 1 | | fancyTags | | 0 | "Quinn muttered (mutter)" |
| | dialogueSentences | 42 | | tagDensity | 0.286 | | leniency | 0.571 | | rawRatio | 0.083 | | effectiveRatio | 0.048 | |