| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 11 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 44 | | tagDensity | 0.25 | | leniency | 0.5 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 97.39% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1916 | | 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) | |
| 76.51% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1916 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "pulse" | | 1 | "scanned" | | 2 | "flickered" | | 3 | "whisper" | | 4 | "calculated" | | 5 | "mechanical" | | 6 | "silence" | | 7 | "dancing" | | 8 | "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 | 173 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 173 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 206 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 42 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1913 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 12 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 80 | | wordCount | 1580 | | uniqueNames | 26 | | maxNameDensity | 1.65 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Quinn" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Harlow | 1 | | Quinn | 26 | | Old | 1 | | Compton | 1 | | Street | 3 | | Herrera | 1 | | Saint | 1 | | Christopher | 1 | | Tomás | 19 | | Brewer | 1 | | Rupert | 1 | | Chinatown | 1 | | Euston | 1 | | Road | 1 | | Italian | 1 | | Camden | 1 | | Tube | 1 | | Yard | 1 | | Morris | 7 | | Spanish | 1 | | Empty-handed | 1 | | Market | 2 | | Veil | 1 | | Rain | 3 |
| | persons | | 0 | "Raven" | | 1 | "Harlow" | | 2 | "Quinn" | | 3 | "Herrera" | | 4 | "Saint" | | 5 | "Christopher" | | 6 | "Tomás" | | 7 | "Morris" | | 8 | "Empty-handed" | | 9 | "Market" |
| | places | | 0 | "Old" | | 1 | "Compton" | | 2 | "Street" | | 3 | "Brewer" | | 4 | "Rupert" | | 5 | "Chinatown" | | 6 | "Euston" | | 7 | "Road" | | 8 | "Italian" | | 9 | "Yard" | | 10 | "Spanish" | | 11 | "Veil" |
| | globalScore | 0.677 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 103 | | glossingSentenceCount | 1 | | matches | | 0 | "seemed wrong too wide, too still" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1913 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 206 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 81 | | mean | 23.62 | | std | 20.81 | | cv | 0.881 | | sampleLengths | | 0 | 75 | | 1 | 6 | | 2 | 55 | | 3 | 3 | | 4 | 16 | | 5 | 2 | | 6 | 34 | | 7 | 15 | | 8 | 53 | | 9 | 14 | | 10 | 5 | | 11 | 61 | | 12 | 46 | | 13 | 60 | | 14 | 16 | | 15 | 18 | | 16 | 7 | | 17 | 10 | | 18 | 6 | | 19 | 35 | | 20 | 36 | | 21 | 8 | | 22 | 4 | | 23 | 34 | | 24 | 4 | | 25 | 45 | | 26 | 5 | | 27 | 20 | | 28 | 3 | | 29 | 70 | | 30 | 15 | | 31 | 53 | | 32 | 8 | | 33 | 12 | | 34 | 2 | | 35 | 1 | | 36 | 60 | | 37 | 7 | | 38 | 2 | | 39 | 30 | | 40 | 22 | | 41 | 34 | | 42 | 4 | | 43 | 31 | | 44 | 5 | | 45 | 4 | | 46 | 64 | | 47 | 65 | | 48 | 27 | | 49 | 2 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 173 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 298 | | matches | | 0 | "wasn’t fleeing" | | 1 | "was funneling" | | 2 | "was coming" |
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| 45.77% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 6 | | flaggedSentences | 7 | | totalSentences | 206 | | ratio | 0.034 | | matches | | 0 | "A night bus exhaled at the stop; Tomás slipped along its blind side while passengers folded themselves out into the rain." | | 1 | "Quinn’s shoe came down on vinegar and slid; she caught a lamp-post, barked her knuckles, kept going." | | 2 | "In the stutter between bulbs, his pupils seemed wrong—too wide, too still." | | 3 | "Stalls unfolded where no stalls could fit: a butcher’s hook hung with pale fish that had too many eyes; a woman in moth wings selling jars of storm; a man with antlers wrapped in fairy lights counting teeth into a brass bowl." | | 4 | "A pouch at his belt spilled when his elbow caught the boarding; three bone tokens clicked across concrete into the gutter." | | 5 | "Tomás’s expression changed first—alarm stripped of performance." | | 6 | "The Market did that for him; the boards leaned inward, the chain curled away from her boots, the threshold waited with the patience of a held breath." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1586 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 41 | | adverbRatio | 0.025851197982345524 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.0037831021437578815 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 206 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 206 | | mean | 9.29 | | std | 6.73 | | cv | 0.725 | | sampleLengths | | 0 | 16 | | 1 | 24 | | 2 | 9 | | 3 | 11 | | 4 | 5 | | 5 | 10 | | 6 | 6 | | 7 | 17 | | 8 | 18 | | 9 | 14 | | 10 | 4 | | 11 | 2 | | 12 | 3 | | 13 | 5 | | 14 | 11 | | 15 | 2 | | 16 | 19 | | 17 | 9 | | 18 | 6 | | 19 | 15 | | 20 | 4 | | 21 | 8 | | 22 | 10 | | 23 | 14 | | 24 | 11 | | 25 | 6 | | 26 | 9 | | 27 | 5 | | 28 | 5 | | 29 | 4 | | 30 | 21 | | 31 | 13 | | 32 | 23 | | 33 | 17 | | 34 | 4 | | 35 | 3 | | 36 | 5 | | 37 | 17 | | 38 | 8 | | 39 | 21 | | 40 | 20 | | 41 | 11 | | 42 | 2 | | 43 | 6 | | 44 | 5 | | 45 | 3 | | 46 | 10 | | 47 | 8 | | 48 | 7 | | 49 | 10 |
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| 56.15% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 11 | | diversityRatio | 0.36893203883495146 | | totalSentences | 206 | | uniqueOpeners | 76 | |
| 64.10% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 156 | | matches | | 0 | "Then she caught the canvas" | | 1 | "Somewhere deeper, glass sang." | | 2 | "Then she stepped down into" |
| | ratio | 0.019 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 40 | | totalSentences | 156 | | matches | | 0 | "He carried a canvas satchel" | | 1 | "His Saint Christopher medal flashed" | | 2 | "He scanned the street." | | 3 | "His face closed." | | 4 | "He cut left through the" | | 5 | "Her radio crackled into her" | | 6 | "He tore free without looking" | | 7 | "He answered by running harder." | | 8 | "They hit Brewer Street." | | 9 | "She parted bodies with her" | | 10 | "He was already at the" | | 11 | "His heel glanced off her" | | 12 | "She held on." | | 13 | "His voice came down through" | | 14 | "She yanked him off the" | | 15 | "They crashed into bins." | | 16 | "He looked past her toward" | | 17 | "He broke left again." | | 18 | "She caught his sleeve, heard" | | 19 | "He backed through the yard" |
| | ratio | 0.256 | |
| 49.74% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 128 | | totalSentences | 156 | | matches | | 0 | "Rain needled the green neon" | | 1 | "Detective Harlow Quinn stood under" | | 2 | "Soho breathed around her in" | | 3 | "A minicab idled at the" | | 4 | "Drunks argued over an umbrella." | | 5 | "Nobody looked twice at the" | | 6 | "Tomás Herrera came out first," | | 7 | "He carried a canvas satchel" | | 8 | "His Saint Christopher medal flashed" | | 9 | "He scanned the street." | | 10 | "His face closed." | | 11 | "Quinn stepped off the kerb." | | 12 | "He cut left through the" | | 13 | "Quinn chased, shoes hammering pooled" | | 14 | "Her radio crackled into her" | | 15 | "Static ate the rest." | | 16 | "A delivery scooter burst from" | | 17 | "Quinn shoved off its wing" | | 18 | "The tape snapped across his" | | 19 | "He tore free without looking" |
| | ratio | 0.821 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 156 | | matches | (empty) | | ratio | 0 | |
| 98.21% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 64 | | technicalSentenceCount | 4 | | matches | | 0 | "Inside, beyond boards that had stood sealed through her whole career, a staircase descended." | | 1 | "Stalls unfolded where no stalls could fit: a butcher’s hook hung with pale fish that had too many eyes; a woman in moth wings selling jars of storm; a man with …" | | 2 | "One stopped against Quinn’s shoe, wet and warm as if recently worn next to skin." | | 3 | "Photograph the chain that had unthreaded itself and bag the impossible with tweezers." |
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| 79.55% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 11 | | uselessAdditionCount | 1 | | matches | | 0 | "Quinn shouted, breath burning" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 44 | | tagDensity | 0.114 | | leniency | 0.227 | | rawRatio | 0.2 | | effectiveRatio | 0.045 | |