| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 17 | | tagDensity | 0.059 | | leniency | 0.118 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1176 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 31.97% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1176 | | totalAiIsms | 16 | | found | | | highlights | | 0 | "maw" | | 1 | "gloom" | | 2 | "footsteps" | | 3 | "echoed" | | 4 | "silk" | | 5 | "silence" | | 6 | "vibrated" | | 7 | "weight" | | 8 | "scanning" | | 9 | "rhythmic" | | 10 | "velvet" | | 11 | "familiar" | | 12 | "flickered" | | 13 | "racing" |
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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 | 1 | | narrationSentences | 103 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 103 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 119 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 28 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1175 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 0 | | matches | (empty) | |
| 33.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 29 | | wordCount | 1079 | | uniqueNames | 9 | | maxNameDensity | 1.95 | | worstName | "Quinn" | | maxWindowNameDensity | 4 | | worstWindowName | "Quinn" | | discoveredNames | | Camden | 1 | | Harlow | 1 | | Quinn | 21 | | Tube | 1 | | Morris | 1 | | Metropolitan | 1 | | Police | 1 | | Veil | 1 | | Market | 1 |
| | persons | | 0 | "Camden" | | 1 | "Harlow" | | 2 | "Quinn" | | 3 | "Morris" | | 4 | "Police" | | 5 | "Market" |
| | places | (empty) | | globalScore | 0.527 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 78 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1175 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 119 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 50 | | mean | 23.5 | | std | 19.37 | | cv | 0.824 | | sampleLengths | | 0 | 75 | | 1 | 46 | | 2 | 32 | | 3 | 2 | | 4 | 27 | | 5 | 50 | | 6 | 44 | | 7 | 11 | | 8 | 53 | | 9 | 25 | | 10 | 3 | | 11 | 40 | | 12 | 27 | | 13 | 14 | | 14 | 4 | | 15 | 32 | | 16 | 1 | | 17 | 18 | | 18 | 6 | | 19 | 21 | | 20 | 8 | | 21 | 55 | | 22 | 45 | | 23 | 15 | | 24 | 13 | | 25 | 72 | | 26 | 11 | | 27 | 8 | | 28 | 9 | | 29 | 5 | | 30 | 42 | | 31 | 5 | | 32 | 13 | | 33 | 5 | | 34 | 47 | | 35 | 18 | | 36 | 26 | | 37 | 1 | | 38 | 34 | | 39 | 29 | | 40 | 6 | | 41 | 11 | | 42 | 7 | | 43 | 33 | | 44 | 8 | | 45 | 31 | | 46 | 3 | | 47 | 9 | | 48 | 14 | | 49 | 61 |
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| 98.45% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 103 | | matches | | 0 | "been scrubbed" | | 1 | "were signed" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 185 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 119 | | ratio | 0.008 | | matches | | 0 | "She remembered the way his office had looked the day he vanished—the overturned chair, the smell of sulfur, the silence that had haunted her for three years." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1086 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 13 | | adverbRatio | 0.011970534069981584 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.0009208103130755065 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 119 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 119 | | mean | 9.87 | | std | 5.31 | | cv | 0.538 | | sampleLengths | | 0 | 15 | | 1 | 18 | | 2 | 8 | | 3 | 17 | | 4 | 17 | | 5 | 11 | | 6 | 3 | | 7 | 17 | | 8 | 11 | | 9 | 4 | | 10 | 14 | | 11 | 18 | | 12 | 2 | | 13 | 4 | | 14 | 23 | | 15 | 9 | | 16 | 3 | | 17 | 15 | | 18 | 11 | | 19 | 12 | | 20 | 14 | | 21 | 12 | | 22 | 3 | | 23 | 15 | | 24 | 7 | | 25 | 4 | | 26 | 10 | | 27 | 13 | | 28 | 15 | | 29 | 15 | | 30 | 25 | | 31 | 3 | | 32 | 14 | | 33 | 14 | | 34 | 12 | | 35 | 9 | | 36 | 3 | | 37 | 2 | | 38 | 13 | | 39 | 14 | | 40 | 4 | | 41 | 8 | | 42 | 13 | | 43 | 11 | | 44 | 1 | | 45 | 10 | | 46 | 8 | | 47 | 6 | | 48 | 10 | | 49 | 8 |
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| 39.92% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.29411764705882354 | | totalSentences | 119 | | uniqueOpeners | 35 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 101 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 26 | | totalSentences | 101 | | matches | | 0 | "Her breath came in jagged" | | 1 | "He leaped over a discarded" | | 2 | "She didn't flinch." | | 3 | "Her salt-and-pepper hair plastered against" | | 4 | "She glanced at the worn" | | 5 | "He glanced back, eyes wide" | | 6 | "He ripped open the grate" | | 7 | "She peered down." | | 8 | "She slid down the rungs," | | 9 | "He towered over her, his" | | 10 | "He didn't move." | | 11 | "She looked past the guard." | | 12 | "She thought of DS Morris." | | 13 | "She remembered the way his" | | 14 | "She stepped closer to the" | | 15 | "She looked at the pulsing" | | 16 | "Her heart hammered against her" | | 17 | "She shifted her stance, her" | | 18 | "She reached out and grabbed" | | 19 | "He staggered back, gasping." |
| | ratio | 0.257 | |
| 14.46% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 90 | | totalSentences | 101 | | matches | | 0 | "Detective Harlow Quinn lunged forward," | | 1 | "Her breath came in jagged" | | 2 | "He leaped over a discarded" | | 3 | "Quinn pivoted around a corner," | | 4 | "She didn't flinch." | | 5 | "Her salt-and-pepper hair plastered against" | | 6 | "She glanced at the worn" | | 7 | "The suspect skidded through a" | | 8 | "He glanced back, eyes wide" | | 9 | "The man didn't stop." | | 10 | "He ripped open the grate" | | 11 | "Quinn reached the opening and" | | 12 | "She peered down." | | 13 | "A concrete ladder descended into" | | 14 | "She slid down the rungs," | | 15 | "The suspect’s footsteps echoed ahead," | | 16 | "Quinn kept pace, her hand" | | 17 | "The air shifted." | | 18 | "The smell of sewage faded," | | 19 | "The corridor opened into a" |
| | ratio | 0.891 | |
| 99.01% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 101 | | matches | | 0 | "If she left now, she" | | 1 | "By the time the warrants" |
| | ratio | 0.02 | |
| 56.65% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 58 | | technicalSentenceCount | 7 | | matches | | 0 | "Detective Harlow Quinn lunged forward, her boots slamming into deep puddles that sprayed grey sludge across her trousers." | | 1 | "He leaped over a discarded crate, his silhouette flickering under the buzzing orange glow of a streetlamp." | | 2 | "A concrete ladder descended into a subterranean gloom that smelled of ancient dust and ozone." | | 3 | "The suspect’s footsteps echoed ahead, a rapid staccato that bounced off the damp walls." | | 4 | "Vendors hawked jars of shimmering liquids and rusted blades that hummed with a low, vibration." | | 5 | "She remembered the way his office had looked the day he vanished—the overturned chair, the smell of sulfur, the silence that had haunted her for three years." | | 6 | "Her heart hammered against her ribs, a rhythmic drumming that matched the rain above." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 17 | | tagDensity | 0.059 | | leniency | 0.118 | | rawRatio | 0 | | effectiveRatio | 0 | |