| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 19 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 41 | | tagDensity | 0.463 | | leniency | 0.927 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 88.56% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1749 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "slightly" | | 1 | "very" | | 2 | "slowly" |
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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) | |
| 79.99% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1749 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "warmth" | | 1 | "scanned" | | 2 | "traced" | | 3 | "glint" | | 4 | "etched" | | 5 | "database" |
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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 | 137 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 137 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 159 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 39 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1766 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 15 | | unquotedAttributions | 0 | | matches | (empty) | |
| 92.03% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 62 | | wordCount | 1380 | | uniqueNames | 25 | | maxNameDensity | 1.16 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Transport | 1 | | London | 1 | | Harlow | 1 | | Quinn | 16 | | Inspector | 1 | | Marcus | 1 | | Webb | 12 | | Underground | 1 | | Camden | 3 | | North | 1 | | Tube | 1 | | Northern | 1 | | Town | 1 | | Chalk | 1 | | Farm | 1 | | English | 1 | | Latin | 1 | | Morris | 4 | | Elliot | 3 | | Greaves | 3 | | Flask | 1 | | Walk | 1 | | Bermondsey | 1 | | Tuesday | 1 | | Three | 3 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Inspector" | | 3 | "Marcus" | | 4 | "Webb" | | 5 | "North" | | 6 | "Morris" | | 7 | "Elliot" | | 8 | "Greaves" | | 9 | "Three" |
| | places | | 0 | "London" | | 1 | "Camden" | | 2 | "Town" | | 3 | "Chalk" | | 4 | "Farm" | | 5 | "Bermondsey" |
| | globalScore | 0.92 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 94 | | glossingSentenceCount | 1 | | matches | | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1766 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 159 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 50 | | mean | 35.32 | | std | 29.18 | | cv | 0.826 | | sampleLengths | | 0 | 68 | | 1 | 51 | | 2 | 105 | | 3 | 8 | | 4 | 31 | | 5 | 63 | | 6 | 6 | | 7 | 78 | | 8 | 24 | | 9 | 70 | | 10 | 5 | | 11 | 38 | | 12 | 3 | | 13 | 41 | | 14 | 77 | | 15 | 4 | | 16 | 6 | | 17 | 4 | | 18 | 5 | | 19 | 9 | | 20 | 80 | | 21 | 24 | | 22 | 81 | | 23 | 10 | | 24 | 12 | | 25 | 44 | | 26 | 91 | | 27 | 54 | | 28 | 5 | | 29 | 17 | | 30 | 3 | | 31 | 74 | | 32 | 22 | | 33 | 89 | | 34 | 9 | | 35 | 33 | | 36 | 17 | | 37 | 32 | | 38 | 22 | | 39 | 47 | | 40 | 3 | | 41 | 36 | | 42 | 8 | | 43 | 50 | | 44 | 51 | | 45 | 15 | | 46 | 66 | | 47 | 58 | | 48 | 7 | | 49 | 10 |
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| 92.46% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 137 | | matches | | 0 | "been sealed" | | 1 | "were folded" | | 2 | "been moved" | | 3 | "was etched" | | 4 | "been found" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 236 | | matches | | 0 | "was, standing" | | 1 | "was chasing" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 13 | | semicolonCount | 0 | | flaggedSentences | 12 | | totalSentences | 159 | | ratio | 0.075 | | matches | | 0 | "Of course it was — the station had been sealed since 1997, or so Transport for London would have you believe." | | 1 | "The air had a sweetness to it — not rot, something else." | | 2 | "His face held an expression that took Quinn a moment to name — not fear, not pain." | | 3 | "His skin was pale but not the pallor of death — he looked more drained than dead, as though someone had pulled the warmth out of him through his pores." | | 4 | "The symbol stared back at her from the dead man's neck — patient, indifferent." | | 5 | "Near the body, the ballast stones between the rails were disturbed — not scattered, arranged." | | 6 | "Something caught the edge of her torch beam — a glint, metallic, small." | | 7 | "The casing was etched with fine, interlocking lines — not decorative." | | 8 | "He'd been running something — a case she still didn't have the full picture of — and the closer she got to the truth, the further it pulled away from her, like a shore receding from a boat." | | 9 | "The symbol on his neck stared up at her from the gap in his collar — the circle, the line, the three marks like compass points." | | 10 | "She breathed in diesel and coffee and rain-wet pavement — ordinary air, thick with the noise of a city that didn't know what lay beneath its feet." | | 11 | "The sigils on the casing caught the light and seemed to shift — or maybe it was just the angle." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 708 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 17 | | adverbRatio | 0.02401129943502825 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.007062146892655367 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 159 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 159 | | mean | 11.11 | | std | 7.55 | | cv | 0.68 | | sampleLengths | | 0 | 4 | | 1 | 21 | | 2 | 24 | | 3 | 19 | | 4 | 20 | | 5 | 23 | | 6 | 8 | | 7 | 14 | | 8 | 27 | | 9 | 8 | | 10 | 11 | | 11 | 25 | | 12 | 1 | | 13 | 11 | | 14 | 8 | | 15 | 8 | | 16 | 7 | | 17 | 19 | | 18 | 5 | | 19 | 4 | | 20 | 12 | | 21 | 6 | | 22 | 8 | | 23 | 15 | | 24 | 9 | | 25 | 9 | | 26 | 6 | | 27 | 1 | | 28 | 2 | | 29 | 11 | | 30 | 6 | | 31 | 20 | | 32 | 17 | | 33 | 1 | | 34 | 20 | | 35 | 11 | | 36 | 13 | | 37 | 5 | | 38 | 5 | | 39 | 11 | | 40 | 30 | | 41 | 9 | | 42 | 1 | | 43 | 8 | | 44 | 1 | | 45 | 5 | | 46 | 10 | | 47 | 12 | | 48 | 16 | | 49 | 3 |
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| 68.76% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.44654088050314467 | | totalSentences | 159 | | uniqueOpeners | 71 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 6 | | totalSentences | 118 | | matches | | 0 | "Of course it was —" | | 1 | "Just a single needle, black" | | 2 | "Maybe he was right." | | 3 | "Maybe she'd been chasing ghosts." | | 4 | "Still pointing down." | | 5 | "Still pointing at whatever Elliot" |
| | ratio | 0.051 | |
| 91.19% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 38 | | totalSentences | 118 | | matches | | 0 | "Her torch beam cut a" | | 1 | "He stood at the far" | | 2 | "She'd spent thirty minutes on" | | 3 | "It clung to the back" | | 4 | "She pushed past a corroded" | | 5 | "He wore a dark coat," | | 6 | "His hands were folded neatly" | | 7 | "His face held an expression" | | 8 | "She studied the man's face." | | 9 | "His skin was pale but" | | 10 | "She held her hand an" | | 11 | "She noticed something Webb hadn't." | | 12 | "She pulled a pair of" | | 13 | "He moved in." | | 14 | "His eyebrows climbed." | | 15 | "She studied the mark again" | | 16 | "He always did that when" | | 17 | "She walked the length of" | | 18 | "She crouched again and traced" | | 19 | "Her gaze drifted to the" |
| | ratio | 0.322 | |
| 78.64% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 90 | | totalSentences | 118 | | matches | | 0 | "The escalator was dead." | | 1 | "Detective Harlow Quinn descended the" | | 2 | "Her torch beam cut a" | | 3 | "Detective Inspector Marcus Webb's voice" | | 4 | "He stood at the far" | | 5 | "Quinn reached the base of" | | 6 | "The old Underground roundel still" | | 7 | "A sign read CAMDEN NORTH" | | 8 | "She'd spent thirty minutes on" | | 9 | "Webb gestured vaguely toward a" | | 10 | "Quinn crossed the platform." | | 11 | "The air had a sweetness" | | 12 | "It clung to the back" | | 13 | "She pushed past a corroded" | | 14 | "The work light illuminated perhaps" | | 15 | "The body lay across the" | | 16 | "He wore a dark coat," | | 17 | "His hands were folded neatly" | | 18 | "His face held an expression" | | 19 | "Webb said, crouching beside the" |
| | ratio | 0.763 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 118 | | matches | (empty) | | ratio | 0 | |
| 72.60% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 61 | | technicalSentenceCount | 6 | | matches | | 0 | "Her torch beam cut a narrow cone through the damp air, catching motes of dust that drifted like ash." | | 1 | "Wide brown eyes staring straight up at the tunnel ceiling, mouth slightly open, as though someone had interrupted him mid-sentence." | | 2 | "The needle was still locked in its strange direction, pressing toward the earth as though something beneath the tunnel demanded its attention." | | 3 | "Three years of dead ends and locked doors and a case file that thickened with every unanswered question." | | 4 | "She breathed in diesel and coffee and rain-wet pavement — ordinary air, thick with the noise of a city that didn't know what lay beneath its feet." | | 5 | "The verdigris on the brass was uneven, older in the crevices, newer on the flat surfaces, as though someone had handled it often but recently." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 19 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 9 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 41 | | tagDensity | 0.22 | | leniency | 0.439 | | rawRatio | 0 | | effectiveRatio | 0 | |