| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 14 | | tagDensity | 0.214 | | leniency | 0.429 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 90.19% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1019 | | totalAiIsmAdverbs | 2 | | 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) | |
| 46.03% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1019 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "fractured" | | 1 | "pulsed" | | 2 | "echoed" | | 3 | "vibrated" | | 4 | "silence" | | 5 | "flicker" | | 6 | "racing" | | 7 | "resonated" | | 8 | "reminder" | | 9 | "predator" |
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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 | 0 | | narrationSentences | 96 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 96 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 107 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 38 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1016 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 3 | | unquotedAttributions | 0 | | matches | (empty) | |
| 90.22% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 28 | | wordCount | 920 | | uniqueNames | 13 | | maxNameDensity | 1.2 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | London | 2 | | Harlow | 1 | | Quinn | 11 | | Saint | 1 | | Christopher | 1 | | Herrera | 4 | | Brewer | 1 | | Street | 1 | | Raven | 1 | | Nest | 1 | | Underground | 1 | | Transport | 1 | | Morris | 2 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Saint" | | 3 | "Christopher" | | 4 | "Herrera" | | 5 | "Raven" | | 6 | "Transport" | | 7 | "Morris" |
| | places | | 0 | "London" | | 1 | "Brewer" | | 2 | "Street" |
| | globalScore | 0.902 | | windowScore | 1 | |
| 2.94% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 68 | | glossingSentenceCount | 4 | | matches | | 0 | "quite see" | | 1 | "looked like a man fleeing a monster" | | 2 | "It was as if the door, and whatever lay behind it, had never existed" | | 3 | "felt like a lie right now" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.984 | | wordCount | 1016 | | matches | | 0 | "not darkness, but a flickering, sourceless light, the colour of deep amber" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 107 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 30 | | mean | 33.87 | | std | 22.32 | | cv | 0.659 | | sampleLengths | | 0 | 69 | | 1 | 80 | | 2 | 60 | | 3 | 55 | | 4 | 61 | | 5 | 39 | | 6 | 50 | | 7 | 35 | | 8 | 38 | | 9 | 37 | | 10 | 14 | | 11 | 26 | | 12 | 73 | | 13 | 18 | | 14 | 44 | | 15 | 14 | | 16 | 7 | | 17 | 14 | | 18 | 6 | | 19 | 12 | | 20 | 18 | | 21 | 20 | | 22 | 4 | | 23 | 36 | | 24 | 77 | | 25 | 31 | | 26 | 32 | | 27 | 10 | | 28 | 17 | | 29 | 19 |
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| 90.64% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 96 | | matches | | 0 | "was replaced" | | 1 | "was gone" | | 2 | "was broken" | | 3 | "was sworn" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 133 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 107 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 923 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 21 | | adverbRatio | 0.02275189599133261 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.010834236186348862 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 107 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 107 | | mean | 9.5 | | std | 6.34 | | cv | 0.668 | | sampleLengths | | 0 | 11 | | 1 | 17 | | 2 | 23 | | 3 | 18 | | 4 | 12 | | 5 | 21 | | 6 | 21 | | 7 | 6 | | 8 | 2 | | 9 | 18 | | 10 | 20 | | 11 | 9 | | 12 | 20 | | 13 | 3 | | 14 | 8 | | 15 | 5 | | 16 | 17 | | 17 | 8 | | 18 | 16 | | 19 | 9 | | 20 | 9 | | 21 | 8 | | 22 | 16 | | 23 | 7 | | 24 | 5 | | 25 | 16 | | 26 | 5 | | 27 | 8 | | 28 | 7 | | 29 | 9 | | 30 | 10 | | 31 | 13 | | 32 | 17 | | 33 | 7 | | 34 | 13 | | 35 | 11 | | 36 | 6 | | 37 | 8 | | 38 | 10 | | 39 | 17 | | 40 | 21 | | 41 | 17 | | 42 | 2 | | 43 | 2 | | 44 | 5 | | 45 | 11 | | 46 | 6 | | 47 | 5 | | 48 | 3 | | 49 | 1 |
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| 48.60% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 13 | | diversityRatio | 0.3644859813084112 | | totalSentences | 107 | | uniqueOpeners | 39 | |
| 38.31% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 87 | | matches | | 0 | "Then he was gone, disappearing" |
| | ratio | 0.011 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 22 | | totalSentences | 87 | | matches | | 0 | "Her bearing, honed by years" | | 1 | "She ignored the stitch in" | | 2 | "He darted across Brewer Street," | | 3 | "He plunged into the darkness" | | 4 | "He fumbled in his jacket," | | 5 | "He pulled out something small" | | 6 | "He pressed it into a" | | 7 | "He didn’t look like a" | | 8 | "He looked like a man" | | 9 | "She was at the door" | | 10 | "It was a solid slab" | | 11 | "She pounded a fist against" | | 12 | "It was as if the" | | 13 | "It was wrong." | | 14 | "It was the same kind" | | 15 | "Her hand was back on" | | 16 | "She was tall and impossibly" | | 17 | "Her face was pale, her" | | 18 | "Her voice was a low" | | 19 | "It was all here." |
| | ratio | 0.253 | |
| 40.46% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 73 | | totalSentences | 87 | | matches | | 0 | "Rain slicked the London cobblestones" | | 1 | "Detective Harlow Quinn’s breath burned" | | 2 | "The Saint Christopher medallion around" | | 3 | "Quinn’s boots hammered the pavement," | | 4 | "Her bearing, honed by years" | | 5 | "She ignored the stitch in" | | 6 | "The target was all that" | | 7 | "A name that had popped" | | 8 | "He darted across Brewer Street," | | 9 | "Quinn followed, a gap of" | | 10 | "The green neon sign of" | | 11 | "Herrera didn’t hesitate." | | 12 | "He plunged into the darkness" | | 13 | "The alley swallowed him whole." | | 14 | "Quinn followed a moment later," | | 15 | "The world narrowed to this" | | 16 | "The smell of rain on" | | 17 | "Something ancient and earthy, like" | | 18 | "An old, tiled entrance to" | | 19 | "London Transport had sealed these" |
| | ratio | 0.839 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 87 | | matches | (empty) | | ratio | 0 | |
| 87.91% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 39 | | technicalSentenceCount | 3 | | matches | | 0 | "A name that had popped up three times in three different unexplained incidents, a ghost in the system." | | 1 | "He darted across Brewer Street, forcing a black cab to swerve, its horn blaring a mournful protest into the downpour." | | 2 | "A low, constant hum, a vibration that resonated in her teeth." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 3 | | uselessAdditionCount | 1 | | matches | | 0 | "Quinn said, her voice low and steady" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 14 | | tagDensity | 0.071 | | leniency | 0.143 | | rawRatio | 0 | | effectiveRatio | 0 | |