| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 4 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 22 | | tagDensity | 0.182 | | leniency | 0.364 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 96.58% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1460 | | totalAiIsmAdverbs | 1 | | 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) | |
| 72.60% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1460 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "measured" | | 1 | "perfect" | | 2 | "scanned" | | 3 | "footsteps" | | 4 | "traced" | | 5 | "etched" | | 6 | "weight" |
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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 | 86 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 86 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 104 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 57 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1460 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 0 | | matches | (empty) | |
| 74.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 31 | | wordCount | 1062 | | uniqueNames | 6 | | maxNameDensity | 1.51 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Camden | 1 | | Tube | 1 | | Harlow | 1 | | Quinn | 16 | | Lang | 10 | | Rourke | 2 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Lang" | | 3 | "Rourke" |
| | places | (empty) | | globalScore | 0.747 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 69 | | 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 | 1460 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 104 | | matches | | 0 | "walked that way" | | 1 | "followed that drip" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 32 | | mean | 45.63 | | std | 29.9 | | cv | 0.655 | | sampleLengths | | 0 | 63 | | 1 | 40 | | 2 | 21 | | 3 | 18 | | 4 | 132 | | 5 | 29 | | 6 | 32 | | 7 | 90 | | 8 | 9 | | 9 | 91 | | 10 | 73 | | 11 | 9 | | 12 | 64 | | 13 | 55 | | 14 | 5 | | 15 | 57 | | 16 | 79 | | 17 | 26 | | 18 | 33 | | 19 | 13 | | 20 | 76 | | 21 | 62 | | 22 | 9 | | 23 | 10 | | 24 | 61 | | 25 | 47 | | 26 | 14 | | 27 | 61 | | 28 | 61 | | 29 | 57 | | 30 | 15 | | 31 | 48 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 86 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 162 | | matches | (empty) | |
| 5.49% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 5 | | flaggedSentences | 5 | | totalSentences | 104 | | ratio | 0.048 | | matches | | 0 | "One loop wrapped around a disused emergency exit sign; the angles lined up with the rectangular voids at the body." | | 1 | "Quinn lifted the hand gently; the rigidity had already set, yet only the wrist joints flexed." | | 2 | "Quinn placed her own hand beside the print to gauge size; the second print matched her own palm dimensions, but the victim had been a larger man." | | 3 | "The needle did not settle north; it swung once, then fixed toward the deeper end of the corridor." | | 4 | "“Rourke wasn’t killed in the service corridor. The killer brought him here to dispose of him, but the blood on the rail came from Rourke defending himself on the platform first. Someone else intervened, placed an object that left those voids, painted over evidence, and fled through the corridor. The paint isn’t cover-up; it’s a seal.”" |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 528 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 4 | | adverbRatio | 0.007575757575757576 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 104 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 104 | | mean | 14.04 | | std | 9.59 | | cv | 0.683 | | sampleLengths | | 0 | 14 | | 1 | 19 | | 2 | 30 | | 3 | 8 | | 4 | 20 | | 5 | 12 | | 6 | 14 | | 7 | 7 | | 8 | 7 | | 9 | 11 | | 10 | 10 | | 11 | 37 | | 12 | 4 | | 13 | 13 | | 14 | 27 | | 15 | 22 | | 16 | 11 | | 17 | 8 | | 18 | 4 | | 19 | 25 | | 20 | 5 | | 21 | 20 | | 22 | 2 | | 23 | 5 | | 24 | 6 | | 25 | 17 | | 26 | 15 | | 27 | 8 | | 28 | 7 | | 29 | 13 | | 30 | 24 | | 31 | 2 | | 32 | 7 | | 33 | 11 | | 34 | 14 | | 35 | 16 | | 36 | 18 | | 37 | 12 | | 38 | 20 | | 39 | 11 | | 40 | 29 | | 41 | 16 | | 42 | 17 | | 43 | 3 | | 44 | 6 | | 45 | 4 | | 46 | 38 | | 47 | 22 | | 48 | 7 | | 49 | 21 |
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| 59.94% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.36538461538461536 | | totalSentences | 104 | | uniqueOpeners | 38 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 81 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 24 | | totalSentences | 81 | | matches | | 0 | "Her leather watch rode tight" | | 1 | "She paused, hands on hips," | | 2 | "She crossed to the body," | | 3 | "She touched the edge of" | | 4 | "She pointed to the angles" | | 5 | "She rose and scanned the" | | 6 | "It lifted in a thin," | | 7 | "She stepped back and let" | | 8 | "She turned to the body" | | 9 | "She pointed at the floor" | | 10 | "She followed that drip with" | | 11 | "She pressed the edge with" | | 12 | "She recorded the numbers, then" | | 13 | "She straightened and faced the" | | 14 | "She opened the nearest lid" | | 15 | "She tilted the can so" | | 16 | "She moved past the rail," | | 17 | "She shone her torch along" | | 18 | "It ended at the tunnel" | | 19 | "She entered, Lang close behind." |
| | ratio | 0.296 | |
| 27.90% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 70 | | totalSentences | 81 | | matches | | 0 | "The basement level of an" | | 1 | "Detective Harlow Quinn stepped across" | | 2 | "Her leather watch rode tight" | | 3 | "She paused, hands on hips," | | 4 | "The smell of damp concrete" | | 5 | "A colleague in a rumpled" | | 6 | "Quinn kept her eyes on" | | 7 | "The colleague, DI Lang, pushed" | | 8 | "She crossed to the body," | | 9 | "The cuts ran shallow to" | | 10 | "Blood had soaked into the" | | 11 | "She touched the edge of" | | 12 | "The concrete felt colder than" | | 13 | "Lang cleared his throat." | | 14 | "Quinn shook her head once." | | 15 | "She pointed to the angles" | | 16 | "She rose and scanned the" | | 17 | "Graffiti tags had been scratched" | | 18 | "The smell of scorched copper" | | 19 | "Quinn walked that way and" |
| | ratio | 0.864 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 81 | | matches | (empty) | | ratio | 0 | |
| 85.71% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 50 | | technicalSentenceCount | 4 | | matches | | 0 | "The fingers curled inward but the thumb pointed away from the injuries, as though Rourke had been reaching for something on the ground rather than defending aga…" | | 1 | "At the pillar base, the concrete was dry except for a small circular stain of oil that glistened green under torchlight." | | 2 | "The victim’s bloody palm print sat at shoulder height, fingers pointing upward as though he had used the rail to pull himself forward." | | 3 | "The step surface showed faint dust displacement in a straight line leading toward the disused tunnel that ran north, away from the platform." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 4 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | 0 | "Quinn repeated (repeat)" |
| | dialogueSentences | 22 | | tagDensity | 0.045 | | leniency | 0.091 | | rawRatio | 1 | | effectiveRatio | 0.091 | |