| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 4 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 8 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 85.63% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1044 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "very" | | 1 | "slowly" | | 2 | "suddenly" |
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| 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) | |
| 80.84% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1044 | | totalAiIsms | 4 | | found | | | highlights | | 0 | "echo" | | 1 | "flicker" | | 2 | "whisper" | | 3 | "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 | 90 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 90 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 94 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 49 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1035 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 27 | | wordCount | 983 | | uniqueNames | 9 | | maxNameDensity | 0.92 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Herrera | 7 | | Soho | 1 | | Camden | 2 | | Tube | 1 | | Morris | 3 | | Tomás | 2 | | Quinn | 9 |
| | persons | | 0 | "Herrera" | | 1 | "Tube" | | 2 | "Morris" | | 3 | "Tomás" | | 4 | "Quinn" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 52 | | glossingSentenceCount | 1 | | matches | | 0 | "felt like a child's toy" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.966 | | wordCount | 1035 | | matches | | 0 | "not the harsh white of utility lamps but something warmer, amber" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 94 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 37 | | mean | 27.97 | | std | 21.21 | | cv | 0.758 | | sampleLengths | | 0 | 46 | | 1 | 2 | | 2 | 11 | | 3 | 46 | | 4 | 56 | | 5 | 7 | | 6 | 13 | | 7 | 54 | | 8 | 4 | | 9 | 37 | | 10 | 9 | | 11 | 27 | | 12 | 40 | | 13 | 65 | | 14 | 11 | | 15 | 35 | | 16 | 20 | | 17 | 7 | | 18 | 9 | | 19 | 60 | | 20 | 5 | | 21 | 46 | | 22 | 2 | | 23 | 50 | | 24 | 10 | | 25 | 77 | | 26 | 31 | | 27 | 45 | | 28 | 7 | | 29 | 61 | | 30 | 14 | | 31 | 30 | | 32 | 21 | | 33 | 47 | | 34 | 11 | | 35 | 10 | | 36 | 9 |
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| 97.47% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 90 | | matches | | 0 | "been erected" | | 1 | "was gone" |
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| 80.24% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 167 | | matches | | 0 | "was deciding" | | 1 | "was speaking" | | 2 | "wasn't coming" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 8 | | semicolonCount | 0 | | flaggedSentences | 6 | | totalSentences | 94 | | ratio | 0.064 | | matches | | 0 | "He glanced back—just once—warm brown eyes wide with something past fear." | | 1 | "She drew her torch, swept the beam across the hoarding—an old works sign, faded, half-peeled." | | 2 | "She'd spent three years circling the edge of an answer she couldn't name, and this man—this disgraced paramedic with his saint's medallion and his off-books patients—was the closest she'd come to the centre of it." | | 3 | "The stairs ended at a platform, and the platform should have been empty, sealed, dead—and it wasn't." | | 4 | "The low collective hum of a market—haggling, laughter, the chime of coins." | | 5 | "The clique, the unexplained deaths, the cases that closed themselves before she could pry them open—it all ran down here into this amber-lit hollow beneath the city, and Tomás Herrera had just walked into the heart of it with a casual ease that told her he belonged." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 997 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 22 | | adverbRatio | 0.022066198595787363 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.004012036108324975 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 94 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 94 | | mean | 11.01 | | std | 9.57 | | cv | 0.869 | | sampleLengths | | 0 | 19 | | 1 | 27 | | 2 | 2 | | 3 | 7 | | 4 | 4 | | 5 | 2 | | 6 | 3 | | 7 | 41 | | 8 | 8 | | 9 | 4 | | 10 | 23 | | 11 | 21 | | 12 | 4 | | 13 | 3 | | 14 | 13 | | 15 | 21 | | 16 | 17 | | 17 | 11 | | 18 | 1 | | 19 | 4 | | 20 | 4 | | 21 | 26 | | 22 | 11 | | 23 | 9 | | 24 | 7 | | 25 | 20 | | 26 | 4 | | 27 | 9 | | 28 | 15 | | 29 | 1 | | 30 | 1 | | 31 | 10 | | 32 | 2 | | 33 | 4 | | 34 | 18 | | 35 | 22 | | 36 | 5 | | 37 | 14 | | 38 | 11 | | 39 | 10 | | 40 | 3 | | 41 | 3 | | 42 | 15 | | 43 | 4 | | 44 | 1 | | 45 | 7 | | 46 | 12 | | 47 | 7 | | 48 | 9 | | 49 | 4 |
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| 72.70% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.46808510638297873 | | totalSentences | 94 | | uniqueOpeners | 44 | |
| 90.09% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 74 | | matches | | 0 | "Then he changed direction." | | 1 | "Then she thought about Herrera's" |
| | ratio | 0.027 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 21 | | totalSentences | 74 | | matches | | 0 | "Her voice cracked against the" | | 1 | "They never did." | | 2 | "Her lungs burned in the" | | 3 | "She clipped the corner, palm" | | 4 | "He knew the city." | | 5 | "He glanced back—just once—warm brown" | | 6 | "He was deciding something." | | 7 | "He veered off the main" | | 8 | "He hit a section of" | | 9 | "She drew her torch, swept" | | 10 | "She knew the maps." | | 11 | "She put her hand on" | | 12 | "She keyed her radio." | | 13 | "She thought of Morris." | | 14 | "His easy laugh." | | 15 | "She'd spent three years circling" | | 16 | "Her torch found a stairwell," | | 17 | "He was speaking, fast, low," | | 18 | "Her hand went to her" | | 19 | "She thought about backup that" |
| | ratio | 0.284 | |
| 74.86% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 57 | | totalSentences | 74 | | matches | | 0 | "Quinn watched the man burst" | | 1 | "Her voice cracked against the" | | 2 | "They never did." | | 3 | "Tomás Herrera vaulted a stack" | | 4 | "Quinn's boots found purchase where" | | 5 | "Her lungs burned in the" | | 6 | "She clipped the corner, palm" | | 7 | "He knew the city." | | 8 | "A taxi blared its horn" | | 9 | "Quinn followed two seconds behind," | | 10 | "He glanced back—just once—warm brown" | | 11 | "He was deciding something." | | 12 | "He veered off the main" | | 13 | "Quinn felt the small hard" | | 14 | "He hit a section of" | | 15 | "Quinn pulled up short." | | 16 | "Rain ran cold down the" | | 17 | "She drew her torch, swept" | | 18 | "The gap yawned at her," | | 19 | "She knew the maps." |
| | ratio | 0.77 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 74 | | matches | | 0 | "As if it had felt" | | 1 | "To the reassuring weight of" |
| | ratio | 0.027 | |
| 89.29% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 40 | | technicalSentenceCount | 3 | | matches | | 0 | "Tomás Herrera vaulted a stack of crates outside the kitchen entrance, sent them clattering into the gutter, and bolted down the alley with the loose, economical…" | | 1 | "Herrera's wet footprints led down, fading already, and beneath them an old tiled sign read a station name that hadn't appeared on any line in seventy years." | | 2 | "The clique, the unexplained deaths, the cases that closed themselves before she could pry them open—it all ran down here into this amber-lit hollow beneath the …" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 4 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 25.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 8 | | tagDensity | 0.375 | | leniency | 0.75 | | rawRatio | 0.333 | | effectiveRatio | 0.25 | |