| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 15 | | adverbTagCount | 1 | | adverbTags | | 0 | "Quinn repeated slowly [slowly]" |
| | dialogueSentences | 45 | | tagDensity | 0.333 | | leniency | 0.667 | | rawRatio | 0.067 | | effectiveRatio | 0.044 | |
| 83.36% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1502 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "slightly" | | 1 | "very" | | 2 | "slowly" | | 3 | "completely" |
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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) | |
| 23.44% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1502 | | totalAiIsms | 23 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | |
| | highlights | | 0 | "echoing" | | 1 | "velvet" | | 2 | "synthetic" | | 3 | "glistening" | | 4 | "standard" | | 5 | "weight" | | 6 | "gloom" | | 7 | "etched" | | 8 | "crystalline" | | 9 | "fractured" | | 10 | "shattered" | | 11 | "charm" | | 12 | "traced" | | 13 | "perfect" | | 14 | "efficient" | | 15 | "pulse" | | 16 | "trembled" | | 17 | "amidst" | | 18 | "measured" |
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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 | 1 | | narrationSentences | 96 | | matches | | |
| 98.21% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 96 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 125 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 43 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 1 | | totalWords | 1490 | | ratio | 0.001 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 52 | | wordCount | 991 | | uniqueNames | 17 | | maxNameDensity | 1.61 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Quinn" | | discoveredNames | | Detective | 2 | | Harlow | 1 | | Quinn | 16 | | Veil | 3 | | Market | 2 | | Tube | 1 | | Camden | 1 | | Shade | 1 | | Specialist | 1 | | Paranormal | 1 | | Unit | 1 | | Morris | 2 | | Davies | 7 | | Compass | 1 | | Eva | 7 | | Elara | 1 | | Vance | 4 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Market" | | 3 | "Unit" | | 4 | "Morris" | | 5 | "Davies" | | 6 | "Eva" | | 7 | "Elara" | | 8 | "Vance" |
| | places | | 0 | "Veil" | | 1 | "Specialist" | | 2 | "Compass" |
| | globalScore | 0.693 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 66 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.671 | | wordCount | 1490 | | matches | | 0 | "not pointing down towards the supposed rift, but quivering erratically, as if disturbed" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 125 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 44 | | mean | 33.86 | | std | 25.54 | | cv | 0.754 | | sampleLengths | | 0 | 21 | | 1 | 30 | | 2 | 111 | | 3 | 59 | | 4 | 31 | | 5 | 45 | | 6 | 83 | | 7 | 9 | | 8 | 20 | | 9 | 94 | | 10 | 42 | | 11 | 61 | | 12 | 37 | | 13 | 66 | | 14 | 5 | | 15 | 49 | | 16 | 19 | | 17 | 51 | | 18 | 9 | | 19 | 11 | | 20 | 55 | | 21 | 31 | | 22 | 16 | | 23 | 19 | | 24 | 4 | | 25 | 6 | | 26 | 56 | | 27 | 9 | | 28 | 1 | | 29 | 5 | | 30 | 8 | | 31 | 56 | | 32 | 10 | | 33 | 25 | | 34 | 66 | | 35 | 38 | | 36 | 23 | | 37 | 38 | | 38 | 18 | | 39 | 53 | | 40 | 19 | | 41 | 49 | | 42 | 19 | | 43 | 13 |
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| 97.95% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 96 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 154 | | matches | | 0 | "was beginning" | | 1 | "was staring" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 125 | | ratio | 0.008 | | matches | | 0 | "She traced the glittering trail back to its apparent origin point—a spot directly between where the victim had skidded to a halt and where he had turned." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 998 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 19 | | adverbRatio | 0.01903807615230461 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.0070140280561122245 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 125 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 125 | | mean | 11.92 | | std | 8.37 | | cv | 0.702 | | sampleLengths | | 0 | 21 | | 1 | 16 | | 2 | 14 | | 3 | 8 | | 4 | 10 | | 5 | 20 | | 6 | 28 | | 7 | 14 | | 8 | 19 | | 9 | 12 | | 10 | 15 | | 11 | 14 | | 12 | 11 | | 13 | 19 | | 14 | 16 | | 15 | 15 | | 16 | 18 | | 17 | 11 | | 18 | 16 | | 19 | 12 | | 20 | 5 | | 21 | 3 | | 22 | 9 | | 23 | 11 | | 24 | 8 | | 25 | 2 | | 26 | 20 | | 27 | 4 | | 28 | 9 | | 29 | 9 | | 30 | 10 | | 31 | 10 | | 32 | 16 | | 33 | 29 | | 34 | 24 | | 35 | 25 | | 36 | 12 | | 37 | 30 | | 38 | 9 | | 39 | 15 | | 40 | 6 | | 41 | 20 | | 42 | 5 | | 43 | 6 | | 44 | 4 | | 45 | 33 | | 46 | 9 | | 47 | 13 | | 48 | 8 | | 49 | 7 |
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| 56.00% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.384 | | totalSentences | 125 | | uniqueOpeners | 48 | |
| 77.52% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 86 | | matches | | 0 | "Just more of the crystalline" | | 1 | "Then his throat is torn" |
| | ratio | 0.023 | |
| 75.81% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 31 | | totalSentences | 86 | | matches | | 0 | "She stared at the cobbled" | | 1 | "It moved every full moon," | | 2 | "It was a young man," | | 3 | "His throat was a ruin" | | 4 | "He looked out of place," | | 5 | "Her worn leather satchel, heavy" | | 6 | "She didn’t touch the body." | | 7 | "Her eyes catalogued." | | 8 | "She noted the worn leather" | | 9 | "she said, her voice flat," | | 10 | "She pivoted on her heel," | | 11 | "It led to a narrow" | | 12 | "She’d learned to distrust the" | | 13 | "They were boxes, and she’d" | | 14 | "She walked a slow circle" | | 15 | "Her gaze fixed on the" | | 16 | "It was curled slightly, the" | | 17 | "She leaned closer." | | 18 | "It wasn’t from the ground." | | 19 | "It was in the lines" |
| | ratio | 0.36 | |
| 0.70% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 79 | | totalSentences | 86 | | matches | | 0 | "The compass needle shivered and" | | 1 | "Eva whispered, her round glasses" | | 2 | "Detective Harlow Quinn didn’t look" | | 3 | "She stared at the cobbled" | | 4 | "The Veil Market smelled of" | | 5 | "It moved every full moon," | | 6 | "Stalls of darkwood and rusted" | | 7 | "A Shade merchant watched them" | | 8 | "The air hummed with whispered" | | 9 | "The body lay between a" | | 10 | "It was a young man," | | 11 | "His throat was a ruin" | | 12 | "A uniformed officer from the" | | 13 | "He looked out of place," | | 14 | "Eva said, tucking a curl" | | 15 | "Her worn leather satchel, heavy" | | 16 | "Quinn knelt, the knees of" | | 17 | "She didn’t touch the body." | | 18 | "Her eyes catalogued." | | 19 | "The sharp angle of the" |
| | ratio | 0.919 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 86 | | matches | (empty) | | ratio | 0 | |
| 74.83% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 42 | | technicalSentenceCount | 4 | | matches | | 0 | "It led to a narrow passage between two stalls, a dark alley of crates and dripping pipes that vanished into the station's deeper gloom." | | 1 | "Tiny, fractured shards that caught the light like diamond splinters." | | 2 | "Her mind worked, cold and efficient, slotting pieces into a pattern that was beginning to form a very different picture from the one Davies saw." | | 3 | "The needle trembled, not pointing down towards the supposed rift, but quivering erratically, as if disturbed." |
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| 58.33% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 15 | | uselessAdditionCount | 2 | | matches | | 0 | "she said, her voice flat, military-precise" | | 1 | "Quinn stood, her sharp jaw tightening" |
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| 61.11% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 7 | | fancyCount | 4 | | fancyTags | | 0 | "Eva whispered (whisper)" | | 1 | "Quinn repeated (repeat)" | | 2 | "Quinn murmured (murmur)" | | 3 | "Quinn repeated slowly (repeat)" |
| | dialogueSentences | 45 | | tagDensity | 0.156 | | leniency | 0.311 | | rawRatio | 0.571 | | effectiveRatio | 0.178 | |