| 46.15% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 15 | | adverbTagCount | 3 | | adverbTags | | 0 | "he said simply [simply]" | | 1 | "he said quietly [quietly]" | | 2 | "she said finally [finally]" |
| | dialogueSentences | 39 | | tagDensity | 0.385 | | leniency | 0.769 | | rawRatio | 0.2 | | effectiveRatio | 0.154 | |
| 89.91% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1486 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | |
| 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) | |
| 36.07% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1486 | | totalAiIsms | 19 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | | word | "down her spine" | | count | 1 |
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| | highlights | | 0 | "scanned" | | 1 | "reminder" | | 2 | "calculated" | | 3 | "pulse" | | 4 | "quickened" | | 5 | "echo" | | 6 | "footsteps" | | 7 | "flicked" | | 8 | "oppressive" | | 9 | "could feel" | | 10 | "intensity" | | 11 | "familiar" | | 12 | "throb" | | 13 | "depths" | | 14 | "flickered" | | 15 | "unspoken" | | 16 | "whisper" | | 17 | "chill" | | 18 | "down her spine" |
| |
| 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 | 1 | | narrationSentences | 81 | | matches | | |
| 89.95% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 81 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 105 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 44 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1472 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 20 | | unquotedAttributions | 0 | | matches | (empty) | |
| 71.88% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 42 | | wordCount | 1088 | | uniqueNames | 14 | | maxNameDensity | 1.56 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Soho | 1 | | Harlow | 1 | | Quinn | 17 | | Raven | 4 | | Nest | 4 | | Tube | 1 | | Camden | 1 | | Eastern | 1 | | European | 1 | | Saint | 1 | | Christopher | 1 | | Morris | 3 | | London | 1 | | Herrera | 5 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Raven" | | 3 | "Saint" | | 4 | "Christopher" | | 5 | "Morris" | | 6 | "Herrera" |
| | places | | | globalScore | 0.719 | | windowScore | 0.833 | |
| 74.24% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 66 | | glossingSentenceCount | 2 | | matches | | 0 | "as if reading her thoughts" | | 1 | "equipment that seemed to malfunction whenever she got too close to the truth" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.679 | | wordCount | 1472 | | matches | | 0 | "not of her, but of something else" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 105 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 47 | | mean | 31.32 | | std | 18.15 | | cv | 0.58 | | sampleLengths | | 0 | 70 | | 1 | 64 | | 2 | 70 | | 3 | 46 | | 4 | 44 | | 5 | 46 | | 6 | 49 | | 7 | 48 | | 8 | 31 | | 9 | 20 | | 10 | 14 | | 11 | 17 | | 12 | 43 | | 13 | 23 | | 14 | 49 | | 15 | 11 | | 16 | 40 | | 17 | 10 | | 18 | 5 | | 19 | 24 | | 20 | 14 | | 21 | 8 | | 22 | 25 | | 23 | 36 | | 24 | 15 | | 25 | 34 | | 26 | 52 | | 27 | 6 | | 28 | 23 | | 29 | 31 | | 30 | 44 | | 31 | 4 | | 32 | 47 | | 33 | 57 | | 34 | 38 | | 35 | 7 | | 36 | 10 | | 37 | 9 | | 38 | 34 | | 39 | 40 | | 40 | 41 | | 41 | 51 | | 42 | 20 | | 43 | 4 | | 44 | 34 | | 45 | 21 | | 46 | 43 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 81 | | matches | | |
| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 6 | | totalVerbs | 182 | | matches | | 0 | "was running" | | 1 | "was processing" | | 2 | "were finally starting" | | 3 | "was dying" | | 4 | "were screaming" | | 5 | "was pulling" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 13 | | semicolonCount | 0 | | flaggedSentences | 12 | | totalSentences | 105 | | ratio | 0.114 | | matches | | 0 | "Her worn leather watch ticked steadily against her wrist—a reminder that time was running out, and so was her patience." | | 1 | "The suspect—probably mid-thirties, built like a runner—weaved through the narrow alleyways with an agility that suggested he knew these streets intimately." | | 2 | "Strange things happened down there—things that didn't show up in official reports." | | 3 | "Quinn raised her radio, but static crackled back at her—another sign that this place existed outside normal communication networks." | | 4 | "She could feel eyes watching from the shadows above—rats, probably, though something in her gut whispered otherwise." | | 5 | "\"You're Detective Quinn,\" he said, his voice carrying an accent she couldn't place—maybe Eastern European." | | 6 | "Herrera—she'd heard that name before, associated with a string of missing persons cases that had gone cold." | | 7 | "Around his neck hung a small medallion—a Saint Christopher, she noted, the patron saint of travelers." | | 8 | "She'd never spoken about Morris to anyone—not officially, not unofficially." | | 9 | "He hesitated, and in that moment, Quinn saw genuine fear—not of her, but of something else." | | 10 | "But something else was pulling her forward—the same compulsion that had driven her to pursue Morris's case despite repeated warnings from superiors, the same drive that had led her to infiltrate the Raven's Nest in the first place." | | 11 | "As he disappeared into the tunnels beyond, Quinn stood alone in the darkness, clutching the card and wondering if she'd just made the biggest mistake of her career—or the only move that could possibly lead her to the truth about her partner's death." |
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| 96.26% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1104 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 48 | | adverbRatio | 0.043478260869565216 | | lyAdverbCount | 23 | | lyAdverbRatio | 0.020833333333333332 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 105 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 105 | | mean | 14.02 | | std | 7.76 | | cv | 0.553 | | sampleLengths | | 0 | 26 | | 1 | 20 | | 2 | 24 | | 3 | 24 | | 4 | 20 | | 5 | 20 | | 6 | 21 | | 7 | 14 | | 8 | 17 | | 9 | 18 | | 10 | 9 | | 11 | 16 | | 12 | 21 | | 13 | 3 | | 14 | 14 | | 15 | 15 | | 16 | 12 | | 17 | 21 | | 18 | 25 | | 19 | 14 | | 20 | 19 | | 21 | 16 | | 22 | 18 | | 23 | 13 | | 24 | 17 | | 25 | 8 | | 26 | 20 | | 27 | 2 | | 28 | 1 | | 29 | 15 | | 30 | 5 | | 31 | 11 | | 32 | 3 | | 33 | 11 | | 34 | 6 | | 35 | 10 | | 36 | 17 | | 37 | 16 | | 38 | 8 | | 39 | 15 | | 40 | 6 | | 41 | 22 | | 42 | 16 | | 43 | 5 | | 44 | 8 | | 45 | 3 | | 46 | 3 | | 47 | 15 | | 48 | 2 | | 49 | 20 |
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| 73.33% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.45714285714285713 | | totalSentences | 105 | | uniqueOpeners | 48 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 76 | | matches | (empty) | | ratio | 0 | |
| 83.16% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 26 | | totalSentences | 76 | | matches | | 0 | "Her brown eyes scanned the" | | 1 | "Her worn leather watch ticked" | | 2 | "She'd clocked eighteen years on" | | 3 | "She rounded a corner and" | | 4 | "She followed, her boots splashing" | | 5 | "She holstered the device and" | | 6 | "She could feel eyes watching" | | 7 | "he said, his voice carrying" | | 8 | "she replied, keeping her tone" | | 9 | "He glanced over his shoulder" | | 10 | "he continued, as if reading" | | 11 | "She studied him more carefully" | | 12 | "he said simply" | | 13 | "She'd lost her partner, DS" | | 14 | "she stated, stepping closer" | | 15 | "His eyes locked onto hers" | | 16 | "She'd never spoken about Morris" | | 17 | "He hesitated, and in that" | | 18 | "Her flashlight beam flickered, and" | | 19 | "She'd learned early in her" |
| | ratio | 0.342 | |
| 58.68% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 61 | | totalSentences | 76 | | matches | | 0 | "The rain had turned the" | | 1 | "Detective Harlow Quinn pulled her" | | 2 | "Her brown eyes scanned the" | | 3 | "The place reeked of trouble," | | 4 | "Her worn leather watch ticked" | | 5 | "The suspect—probably mid-thirties, built like" | | 6 | "Quinn matched his pace, her" | | 7 | "She'd clocked eighteen years on" | | 8 | "This was someone who understood" | | 9 | "She rounded a corner and" | | 10 | "The man had stopped dead," | | 11 | "Quinn's pulse quickened." | | 12 | "That area had been sealed" | | 13 | "The city maintained it as" | | 14 | "She followed, her boots splashing" | | 15 | "The wind carried the scent" | | 16 | "Quinn raised her radio, but" | | 17 | "She holstered the device and" | | 18 | "The stairs descended into darkness," | | 19 | "The suspect was already halfway" |
| | ratio | 0.803 | |
| 65.79% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 76 | | matches | | 0 | "Whether that illumination would reveal" |
| | ratio | 0.013 | |
| 48.52% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 53 | | technicalSentenceCount | 7 | | matches | | 0 | "This was someone who understood consequences, someone who'd made a calculated decision to flee rather than face questioning." | | 1 | "Late twenties, olive skin, a scar running along his left forearm that looked fresh despite his claim of being a medical professional." | | 2 | "The same word that had haunted her dreams and driven her obsession with the underground networks operating beneath London's surface." | | 3 | "Three years of dead ends, false leads, and whispered rumors about things that shouldn't exist." | | 4 | "The battery was dying, just like every other piece of equipment that seemed to malfunction whenever she got too close to the truth." | | 5 | "But something else was pulling her forward—the same compulsion that had driven her to pursue Morris's case despite repeated warnings from superiors, the same dr…" | | 6 | "As he disappeared into the tunnels beyond, Quinn stood alone in the darkness, clutching the card and wondering if she'd just made the biggest mistake of her car…" |
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| 58.33% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 15 | | uselessAdditionCount | 2 | | matches | | 0 | "he continued, as if reading her thoughts" | | 1 | "She stepped, her voice dropping to a whisper" |
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| 73.08% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 10 | | fancyCount | 3 | | fancyTags | | 0 | "he continued (continue)" | | 1 | "she stated (state)" | | 2 | "she observed (observe)" |
| | dialogueSentences | 39 | | tagDensity | 0.256 | | leniency | 0.513 | | rawRatio | 0.3 | | effectiveRatio | 0.154 | |