| 91.89% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 16 | | adverbTagCount | 2 | | adverbTags | | 0 | "Quinn’s command snapped like [like]" | | 1 | "Eva stepped back [back]" |
| | dialogueSentences | 37 | | tagDensity | 0.432 | | leniency | 0.865 | | rawRatio | 0.125 | | effectiveRatio | 0.108 | |
| 89.44% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1421 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "nervously" | | 1 | "really" | | 2 | "truly" |
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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) | |
| 22.59% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1421 | | totalAiIsms | 22 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | | word | "the last thing" | | count | 1 |
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| | highlights | | 0 | "traced" | | 1 | "fractured" | | 2 | "standard" | | 3 | "dancing" | | 4 | "silence" | | 5 | "pristine" | | 6 | "rhythmic" | | 7 | "scanning" | | 8 | "calculated" | | 9 | "vibrated" | | 10 | "echoes" | | 11 | "etched" | | 12 | "gloom" | | 13 | "magnetic" | | 14 | "shattered" | | 15 | "pulsed" | | 16 | "depths" | | 17 | "echoed" | | 18 | "the last thing" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 97 | | matches | (empty) | |
| 69.22% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 4 | | narrationSentences | 97 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 118 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 35 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1421 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 42 | | wordCount | 1095 | | uniqueNames | 9 | | maxNameDensity | 1.55 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Eva" | | discoveredNames | | Camden | 1 | | Tube | 1 | | Miller | 11 | | Quinn | 17 | | Italian | 1 | | British | 1 | | Museum | 1 | | Kowalski | 2 | | Eva | 7 |
| | persons | | 0 | "Miller" | | 1 | "Quinn" | | 2 | "Kowalski" | | 3 | "Eva" |
| | places | | | globalScore | 0.724 | | windowScore | 0.667 | |
| 60.71% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 84 | | glossingSentenceCount | 3 | | matches | | 0 | "sigil that seemed to swallow the torchlight" | | 1 | "looked like a halo of wire in the violet" | | 2 | "looked like a student who had lost her wa" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.704 | | wordCount | 1421 | | matches | | 0 | "not by the body this time, but by a small, circular indentation in the dust near the archwa" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 118 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 48 | | mean | 29.6 | | std | 17.15 | | cv | 0.579 | | sampleLengths | | 0 | 68 | | 1 | 39 | | 2 | 36 | | 3 | 12 | | 4 | 41 | | 5 | 37 | | 6 | 35 | | 7 | 49 | | 8 | 18 | | 9 | 47 | | 10 | 11 | | 11 | 40 | | 12 | 14 | | 13 | 19 | | 14 | 49 | | 15 | 34 | | 16 | 29 | | 17 | 27 | | 18 | 4 | | 19 | 6 | | 20 | 51 | | 21 | 47 | | 22 | 47 | | 23 | 9 | | 24 | 17 | | 25 | 48 | | 26 | 7 | | 27 | 46 | | 28 | 17 | | 29 | 8 | | 30 | 6 | | 31 | 44 | | 32 | 6 | | 33 | 55 | | 34 | 37 | | 35 | 20 | | 36 | 12 | | 37 | 32 | | 38 | 3 | | 39 | 31 | | 40 | 17 | | 41 | 54 | | 42 | 8 | | 43 | 47 | | 44 | 13 | | 45 | 42 | | 46 | 38 | | 47 | 44 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 97 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 177 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 118 | | ratio | 0 | | matches | (empty) | |
| 88.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1107 | | adjectiveStacks | 2 | | stackExamples | | 0 | "tiny, ivory-coloured sliver" | | 1 | "long, grey translucent hand" |
| | adverbCount | 28 | | adverbRatio | 0.025293586269196026 | | lyAdverbCount | 12 | | lyAdverbRatio | 0.01084010840108401 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 118 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 118 | | mean | 12.04 | | std | 5.71 | | cv | 0.474 | | sampleLengths | | 0 | 12 | | 1 | 12 | | 2 | 21 | | 3 | 23 | | 4 | 19 | | 5 | 20 | | 6 | 13 | | 7 | 13 | | 8 | 1 | | 9 | 9 | | 10 | 12 | | 11 | 11 | | 12 | 6 | | 13 | 8 | | 14 | 16 | | 15 | 15 | | 16 | 22 | | 17 | 35 | | 18 | 14 | | 19 | 12 | | 20 | 12 | | 21 | 11 | | 22 | 10 | | 23 | 8 | | 24 | 21 | | 25 | 12 | | 26 | 9 | | 27 | 5 | | 28 | 11 | | 29 | 11 | | 30 | 12 | | 31 | 17 | | 32 | 14 | | 33 | 19 | | 34 | 8 | | 35 | 13 | | 36 | 12 | | 37 | 16 | | 38 | 11 | | 39 | 23 | | 40 | 10 | | 41 | 19 | | 42 | 2 | | 43 | 11 | | 44 | 14 | | 45 | 4 | | 46 | 6 | | 47 | 5 | | 48 | 18 | | 49 | 12 |
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| 43.30% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 11 | | diversityRatio | 0.3162393162393162 | | totalSentences | 117 | | uniqueOpeners | 37 | |
| 71.68% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 93 | | matches | | 0 | "Specifically, it reminded her of" | | 1 | "Then, the ground beneath Quinn’s" |
| | ratio | 0.022 | |
| 78.06% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 33 | | totalSentences | 93 | | matches | | 0 | "She didn't need a coroner" | | 1 | "She adjusted the worn leather" | | 2 | "He peered at the victim’s" | | 3 | "They remained pristine, save for" | | 4 | "She moved with a calculated" | | 5 | "She stopped near a bricked-up" | | 6 | "She reached into her pocket" | | 7 | "She retrieved a tiny, ivory-coloured" | | 8 | "It wasn't stone or plastic." | | 9 | "It bore a microscopic, etched" | | 10 | "She stood up and approached" | | 11 | "Her sharp jaw set as" | | 12 | "She ran her hand over" | | 13 | "He swung his torch toward" | | 14 | "He sniffed the air tentatively." | | 15 | "It was the rich, cloying" | | 16 | "It was a smell that" | | 17 | "She knew that scent." | | 18 | "It reminded her of the" | | 19 | "She turned her attention back" |
| | ratio | 0.355 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 86 | | totalSentences | 93 | | matches | | 0 | "Quinn’s thumb traced the jagged" | | 1 | "She didn't need a coroner" | | 2 | "The man lay sprawled across" | | 3 | "DS Miller stood a few" | | 4 | "Quinn rose to her full" | | 5 | "She adjusted the worn leather" | | 6 | "The silence in the tunnel" | | 7 | "Miller stepped closer, the soles" | | 8 | "He peered at the victim’s" | | 9 | "The man wore expensive, handmade" | | 10 | "They remained pristine, save for" | | 11 | "Quinn’s voice carried the flat," | | 12 | "Quinn ignored him, her brown" | | 13 | "She moved with a calculated" | | 14 | "She stopped near a bricked-up" | | 15 | "A faint, rhythmic hum vibrated" | | 16 | "Miller suggested, though the air" | | 17 | "Quinn knelt again, not by" | | 18 | "She reached into her pocket" | | 19 | "She retrieved a tiny, ivory-coloured" |
| | ratio | 0.925 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 93 | | matches | (empty) | | ratio | 0 | |
| 91.84% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 56 | | technicalSentenceCount | 4 | | matches | | 0 | "Above them, the vaulted ceiling of the abandoned Camden Tube station dripped with a thick, oily sludge that smelled of ozone and rot." | | 1 | "The humming grew louder, a low-frequency thrum that made her teeth ache." | | 2 | "They began to pull a massive, distorted shape through the archway, something that defied the laws of geometry and light." | | 3 | "Then, the ground beneath Quinn’s feet liquidated, and she felt the sickening, weightless sensation of falling into a hole that had no bottom." |
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| 31.25% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 16 | | uselessAdditionCount | 3 | | matches | | 0 | "Miller suggested, though the air remained deathly still" | | 1 | "Eva said, her voice trembling but clear" | | 2 | "Quinn pulled, her movements precise and practiced" |
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| 41.89% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 4 | | fancyTags | | 0 | "Miller suggested (suggest)" | | 1 | "Quinn’s command snapped like (snap)" | | 2 | "Miller whispered (whisper)" | | 3 | "Eva whispered (whisper)" |
| | dialogueSentences | 37 | | tagDensity | 0.162 | | leniency | 0.324 | | rawRatio | 0.667 | | effectiveRatio | 0.216 | |