| 70.97% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 12 | | adverbTagCount | 2 | | adverbTags | | 0 | "Harlow said quietly [quietly]" | | 1 | "she said softly [softly]" |
| | dialogueSentences | 31 | | tagDensity | 0.387 | | leniency | 0.774 | | rawRatio | 0.167 | | effectiveRatio | 0.129 | |
| 49.41% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1779 | | totalAiIsmAdverbs | 18 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | adverb | "deliberately" | | count | 1 |
| | 10 | |
| | highlights | | 0 | "carefully" | | 1 | "slightly" | | 2 | "very" | | 3 | "perfectly" | | 4 | "gently" | | 5 | "lazily" | | 6 | "sharply" | | 7 | "slowly" | | 8 | "quickly" | | 9 | "deliberately" | | 10 | "softly" |
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| 80.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 55.03% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1779 | | totalAiIsms | 16 | | found | | | highlights | | 0 | "silence" | | 1 | "fluttered" | | 2 | "stomach" | | 3 | "scanning" | | 4 | "shimmered" | | 5 | "familiar" | | 6 | "etched" | | 7 | "pulse" | | 8 | "quickened" | | 9 | "weight" | | 10 | "chill" |
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| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
| | 1 | | label | "weight of words/silence" | | count | 1 |
|
| | highlights | | 0 | "eyes widened" | | 1 | "the weight of those words" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 116 | | matches | | |
| 68.97% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 5 | | narrationSentences | 116 | | filterMatches | | | hedgeMatches | | 0 | "tried to" | | 1 | "started to" | | 2 | "seemed to" | | 3 | "happened to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 135 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 56 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 9 | | totalWords | 1770 | | ratio | 0.005 | | matches | | 0 | "The veil is tearing, Quinn. And something’s bleeding through." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 33.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 53 | | wordCount | 1269 | | uniqueNames | 11 | | maxNameDensity | 1.81 | | worstName | "Harlow" | | maxWindowNameDensity | 4 | | worstWindowName | "Harlow" | | discoveredNames | | Tube | 1 | | Camden | 1 | | Harlow | 23 | | Quinn | 4 | | Northern | 1 | | Line | 1 | | Sergeant | 1 | | Patel | 7 | | Morris | 4 | | Kowalski | 1 | | Eva | 9 |
| | persons | | 0 | "Camden" | | 1 | "Harlow" | | 2 | "Quinn" | | 3 | "Sergeant" | | 4 | "Patel" | | 5 | "Morris" | | 6 | "Kowalski" | | 7 | "Eva" |
| | places | (empty) | | globalScore | 0.594 | | windowScore | 0.333 | |
| 0.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 78 | | glossingSentenceCount | 5 | | matches | | 0 | "looked like blood and some kind of black" | | 1 | "as though searching for something that kept moving" | | 2 | "It was as though the blood had been drawn out slowly, deliberately, rather than expelled in panic" | | 3 | "seemed genuine rather than performed" | | 4 | "felt like she was finally moving toward" |
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| 87.01% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.13 | | wordCount | 1770 | | matches | | 0 | "not terror but something closer to awe" | | 1 | "not pointing north, but twitching toward the blocked tunnel entrance as though searc" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 135 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 58 | | mean | 30.52 | | std | 20.35 | | cv | 0.667 | | sampleLengths | | 0 | 86 | | 1 | 49 | | 2 | 58 | | 3 | 23 | | 4 | 7 | | 5 | 11 | | 6 | 64 | | 7 | 45 | | 8 | 33 | | 9 | 48 | | 10 | 8 | | 11 | 57 | | 12 | 72 | | 13 | 39 | | 14 | 9 | | 15 | 34 | | 16 | 71 | | 17 | 2 | | 18 | 42 | | 19 | 9 | | 20 | 25 | | 21 | 42 | | 22 | 32 | | 23 | 6 | | 24 | 24 | | 25 | 17 | | 26 | 13 | | 27 | 65 | | 28 | 51 | | 29 | 24 | | 30 | 37 | | 31 | 56 | | 32 | 9 | | 33 | 20 | | 34 | 42 | | 35 | 16 | | 36 | 25 | | 37 | 30 | | 38 | 4 | | 39 | 36 | | 40 | 14 | | 41 | 70 | | 42 | 40 | | 43 | 13 | | 44 | 34 | | 45 | 26 | | 46 | 29 | | 47 | 5 | | 48 | 6 | | 49 | 2 |
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| 78.04% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 9 | | totalSentences | 116 | | matches | | 0 | "been rigged" | | 1 | "were fixed" | | 2 | "was etched" | | 3 | "been emptied" | | 4 | "been seen" | | 5 | "were discovered" | | 6 | "been drawn" | | 7 | "been sealed" | | 8 | "been trained" | | 9 | "was taken" |
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| 82.53% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 227 | | matches | | 0 | "was inching" | | 1 | "was pointing" | | 2 | "was getting" | | 3 | "was finally moving" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 9 | | semicolonCount | 0 | | flaggedSentences | 7 | | totalSentences | 135 | | ratio | 0.052 | | matches | | 0 | "The air tasted of damp brick, rust, and something sharper—ozone and scorched herbs." | | 1 | "“Uniforms found him during a routine sweep of the derelict stations. No ID yet. Throat’s been cut, but the wound doesn’t look right. Too clean for a knife fight. And there’s this.” He pointed to a series of symbols burned into the concrete around the body—circles intersecting with jagged lines, the edges still faintly smoking." | | 2 | "His eyes—wide, glassy—were fixed on the ceiling as though he had seen something wondrous in his final moments." | | 3 | "She had seen a compass like this before—once, in a locked evidence box from Morris’s last case." | | 4 | "The woman who had been seen near three different crime scenes in the last fourteen months—always arriving just after the bodies were discovered, always with perfectly reasonable explanations." | | 5 | "The wound had bled, yes—enough to stain the victim’s shirt and pool beneath him—but the spray patterns were inconsistent with arterial damage." | | 6 | "Eva’s nervous habit returned—tucking hair, adjusting glasses." |
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| 96.19% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1285 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 57 | | adverbRatio | 0.0443579766536965 | | lyAdverbCount | 20 | | lyAdverbRatio | 0.01556420233463035 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 135 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 135 | | mean | 13.11 | | std | 10.3 | | cv | 0.785 | | sampleLengths | | 0 | 13 | | 1 | 19 | | 2 | 13 | | 3 | 25 | | 4 | 16 | | 5 | 19 | | 6 | 2 | | 7 | 8 | | 8 | 5 | | 9 | 3 | | 10 | 12 | | 11 | 16 | | 12 | 11 | | 13 | 23 | | 14 | 8 | | 15 | 13 | | 16 | 10 | | 17 | 7 | | 18 | 8 | | 19 | 3 | | 20 | 9 | | 21 | 55 | | 22 | 11 | | 23 | 8 | | 24 | 13 | | 25 | 13 | | 26 | 19 | | 27 | 14 | | 28 | 29 | | 29 | 19 | | 30 | 3 | | 31 | 5 | | 32 | 25 | | 33 | 14 | | 34 | 18 | | 35 | 13 | | 36 | 6 | | 37 | 16 | | 38 | 15 | | 39 | 22 | | 40 | 3 | | 41 | 17 | | 42 | 10 | | 43 | 4 | | 44 | 5 | | 45 | 9 | | 46 | 2 | | 47 | 32 | | 48 | 4 | | 49 | 23 |
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| 54.32% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.34814814814814815 | | totalSentences | 135 | | uniqueOpeners | 47 | |
| 31.75% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 105 | | matches | | 0 | "Gently, she pried the fingers" |
| | ratio | 0.01 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 28 | | totalSentences | 105 | | matches | | 0 | "She adjusted the worn leather" | | 1 | "She moved forward with military" | | 2 | "His left hand clutched something" | | 3 | "He glanced up as Harlow" | | 4 | "she said, voice low" | | 5 | "He pointed to a series" | | 6 | "She had seen similar marks" | | 7 | "She reached into her coat" | | 8 | "It crumbled slightly between her" | | 9 | "She studied the body instead." | | 10 | "His eyes—wide, glassy—were fixed on" | | 11 | "She turned her attention to" | | 12 | "She had seen a compass" | | 13 | "She had never believed it." | | 14 | "she asked, keeping her voice" | | 15 | "She clutched a worn leather" | | 16 | "She kept tucking a strand" | | 17 | "Her green eyes widened behind" | | 18 | "She stopped herself" | | 19 | "It was as though the" |
| | ratio | 0.267 | |
| 17.14% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 93 | | totalSentences | 105 | | matches | | 0 | "The abandoned Tube station beneath" | | 1 | "Detective Harlow Quinn stepped off" | | 2 | "The air tasted of damp" | | 3 | "Emergency lights had been rigged" | | 4 | "She adjusted the worn leather" | | 5 | "The call had come in" | | 6 | "Body in the old station." | | 7 | "The moment the dispatcher had" | | 8 | "She moved forward with military" | | 9 | "The victim lay sprawled near" | | 10 | "His left hand clutched something" | | 11 | "Detective Sergeant Patel crouched beside" | | 12 | "He glanced up as Harlow" | | 13 | "she said, voice low" | | 14 | "Patel straightened, wiping his gloved" | | 15 | "He pointed to a series" | | 16 | "Harlow knelt, the sharp line" | | 17 | "The symbols were familiar in" | | 18 | "She had seen similar marks" | | 19 | "The same night everything she" |
| | ratio | 0.886 | |
| 47.62% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 105 | | matches | | 0 | "Now the barrier showed fresh" |
| | ratio | 0.01 | |
| 50.26% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 54 | | technicalSentenceCount | 7 | | matches | | 0 | "The abandoned Tube station beneath Camden hummed with a silence that felt wrong." | | 1 | "Male, mid-thirties, expensive coat now soaked with what looked like blood and some kind of black residue that shimmered faintly under the lights." | | 2 | "His eyes—wide, glassy—were fixed on the ceiling as though he had seen something wondrous in his final moments." | | 3 | "The needle spun lazily, not pointing north, but twitching toward the blocked tunnel entrance as though searching for something that kept moving." | | 4 | "The woman who had been seen near three different crime scenes in the last fourteen months—always arriving just after the bodies were discovered, always with per…" | | 5 | "She looked again at the body, at the compass needle now spinning faster, at the symbols that weren’t quite right, at the way the dead man’s face still held that…" | | 6 | "The abandoned station seemed to hold its breath around them, the blocked tunnel waiting like a mouth that had already swallowed one man whole and was still hung…" |
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| 83.33% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 12 | | uselessAdditionCount | 1 | | matches | | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 8 | | fancyCount | 1 | | fancyTags | | 0 | "Harlow repeated (repeat)" |
| | dialogueSentences | 31 | | tagDensity | 0.258 | | leniency | 0.516 | | rawRatio | 0.125 | | effectiveRatio | 0.065 | |