| 97.44% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 2 | | adverbTags | | 0 | "His lips pulled back [back]" | | 1 | "she said finally [finally]" |
| | dialogueSentences | 39 | | tagDensity | 0.333 | | leniency | 0.667 | | rawRatio | 0.154 | | effectiveRatio | 0.103 | |
| 82.97% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1468 | | totalAiIsmAdverbs | 5 | | found | | 0 | | | 1 | | | 2 | | | 3 | | adverb | "deliberately" | | count | 1 |
|
| | highlights | | 0 | "slowly" | | 1 | "very" | | 2 | "completely" | | 3 | "deliberately" |
| |
| 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) | |
| 59.13% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1468 | | totalAiIsms | 12 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | word | "carried the weight" | | count | 1 |
| | 10 | |
| | highlights | | 0 | "pulsed" | | 1 | "calculating" | | 2 | "dancing" | | 3 | "velvet" | | 4 | "crystalline" | | 5 | "could feel" | | 6 | "gleaming" | | 7 | "familiar" | | 8 | "scanning" | | 9 | "carried the weight" | | 10 | "depths" |
| |
| 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 | 78 | | matches | (empty) | |
| 87.91% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 3 | | narrationSentences | 78 | | filterMatches | (empty) | | hedgeMatches | | 0 | "seemed to" | | 1 | "tried to" | | 2 | "begin to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 101 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 44 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1459 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 31 | | wordCount | 1053 | | uniqueNames | 15 | | maxNameDensity | 0.85 | | worstName | "Harlow" | | maxWindowNameDensity | 2 | | worstWindowName | "Harlow" | | discoveredNames | | Camden | 2 | | Quinn | 1 | | Chalk | 1 | | Farm | 1 | | Road | 1 | | Underground | 1 | | Victorian | 1 | | Veil | 2 | | Market | 4 | | Harlow | 9 | | Spanish | 1 | | Tomás | 4 | | Herrera | 1 | | Saint | 1 | | Christopher | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Market" | | 2 | "Harlow" | | 3 | "Tomás" | | 4 | "Herrera" | | 5 | "Saint" | | 6 | "Christopher" |
| | places | | 0 | "Camden" | | 1 | "Chalk" | | 2 | "Farm" | | 3 | "Road" | | 4 | "Veil" |
| | globalScore | 1 | | windowScore | 1 | |
| 69.35% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 62 | | glossingSentenceCount | 2 | | matches | | 0 | "looked like an abandoned maintenance shaf" | | 1 | "graffiti that seemed to shift at the edges of her vision" |
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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 | 1459 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 101 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 49 | | mean | 29.78 | | std | 20.18 | | cv | 0.678 | | sampleLengths | | 0 | 27 | | 1 | 67 | | 2 | 63 | | 3 | 16 | | 4 | 55 | | 5 | 4 | | 6 | 64 | | 7 | 40 | | 8 | 4 | | 9 | 40 | | 10 | 16 | | 11 | 45 | | 12 | 48 | | 13 | 21 | | 14 | 59 | | 15 | 6 | | 16 | 35 | | 17 | 25 | | 18 | 27 | | 19 | 19 | | 20 | 56 | | 21 | 4 | | 22 | 8 | | 23 | 4 | | 24 | 43 | | 25 | 11 | | 26 | 26 | | 27 | 7 | | 28 | 23 | | 29 | 38 | | 30 | 18 | | 31 | 28 | | 32 | 64 | | 33 | 48 | | 34 | 3 | | 35 | 47 | | 36 | 5 | | 37 | 53 | | 38 | 55 | | 39 | 32 | | 40 | 13 | | 41 | 14 | | 42 | 1 | | 43 | 54 | | 44 | 5 | | 45 | 47 | | 46 | 39 | | 47 | 11 | | 48 | 21 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 78 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 170 | | matches | | 0 | "was hunting" | | 1 | "was running" |
| |
| 1.41% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 7 | | semicolonCount | 0 | | flaggedSentences | 5 | | totalSentences | 101 | | ratio | 0.05 | | matches | | 0 | "He'd been walking along Chalk Farm Road when she'd called out to him, and something in the way he'd looked at her—too long, too calculating—had told her everything she needed to know." | | 1 | "The alley spat her out onto a side street, rain hammering against her leather jacket, and she spotted him again—ducking through the entrance of what looked like an abandoned maintenance shaft for the Underground." | | 2 | "The raw concrete gave way to something older—Victorian brickwork, perhaps, or something that merely resembled it." | | 3 | "People moved between the stalls—some human, some decidedly not—and they looked up as she emerged, their faces flickering in the candlelight." | | 4 | "The Market hummed with activity she couldn't begin to understand—whispers in languages that scraped against her skull, the rustle of wings that might have been cloak or might have been something else, the gleam of eyes in the darkness that watched without blinking." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1063 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 41 | | adverbRatio | 0.03857008466603951 | | lyAdverbCount | 15 | | lyAdverbRatio | 0.014111006585136407 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 101 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 101 | | mean | 14.45 | | std | 10.31 | | cv | 0.714 | | sampleLengths | | 0 | 24 | | 1 | 3 | | 2 | 43 | | 3 | 9 | | 4 | 15 | | 5 | 9 | | 6 | 22 | | 7 | 32 | | 8 | 8 | | 9 | 8 | | 10 | 17 | | 11 | 4 | | 12 | 34 | | 13 | 4 | | 14 | 25 | | 15 | 19 | | 16 | 4 | | 17 | 16 | | 18 | 5 | | 19 | 3 | | 20 | 32 | | 21 | 4 | | 22 | 16 | | 23 | 3 | | 24 | 21 | | 25 | 16 | | 26 | 9 | | 27 | 15 | | 28 | 21 | | 29 | 6 | | 30 | 6 | | 31 | 12 | | 32 | 6 | | 33 | 18 | | 34 | 21 | | 35 | 11 | | 36 | 25 | | 37 | 23 | | 38 | 6 | | 39 | 27 | | 40 | 8 | | 41 | 17 | | 42 | 8 | | 43 | 8 | | 44 | 19 | | 45 | 19 | | 46 | 33 | | 47 | 23 | | 48 | 4 | | 49 | 2 |
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| 51.49% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.3564356435643564 | | totalSentences | 101 | | uniqueOpeners | 36 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 76 | | matches | | 0 | "Then the architecture changed." | | 1 | "Then he turned and melted" | | 2 | "Somewhere in its depths, her" |
| | ratio | 0.039 | |
| 88.42% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 25 | | totalSentences | 76 | | matches | | 0 | "She felt herself sliding, compensated" | | 1 | "He'd been walking along Chalk" | | 2 | "She'd been hunting the clique" | | 3 | "She didn't slow down." | | 4 | "Her flashlight beam cut through" | | 5 | "Her thighs burned." | | 6 | "She reached the bottom of" | | 7 | "Her fingers found only wet" | | 8 | "She didn't have a weapon" | | 9 | "She'd been off-duty when she'd" | | 10 | "She'd followed him into the" | | 11 | "She could feel him slipping" | | 12 | "She took a step forward," | | 13 | "His lips pulled back from" | | 14 | "It was not a pleasant" | | 15 | "She watched the crowd, searching" | | 16 | "He touched her arm again," | | 17 | "She turned to face him" | | 18 | "He glanced past her, scanning" | | 19 | "Her suspect was out there" |
| | ratio | 0.329 | |
| 12.63% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 68 | | totalSentences | 76 | | matches | | 0 | "The rain came down in" | | 1 | "Harlow Quinn ran." | | 2 | "The wet asphalt offered no" | | 3 | "She felt herself sliding, compensated" | | 4 | "The suspect was a hundred" | | 5 | "A man in a dark" | | 6 | "He'd been walking along Chalk" | | 7 | "She'd been hunting the clique" | | 8 | "Tonight, one of them had" | | 9 | "The man cut left, disappearing" | | 10 | "Harlow followed without hesitation." | | 11 | "The alley spat her out" | | 12 | "She didn't slow down." | | 13 | "The shaft descended at a" | | 14 | "Her flashlight beam cut through" | | 15 | "Symbols she didn't recognize." | | 16 | "Names written in languages that" | | 17 | "The stairs went on forever." | | 18 | "Her thighs burned." | | 19 | "The rain became a distant" |
| | ratio | 0.895 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 76 | | matches | (empty) | | ratio | 0 | |
| 40.82% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 35 | | technicalSentenceCount | 5 | | matches | | 0 | "A man in a dark coat, moving with the desperate efficiency of someone who knew the area far better than she did." | | 1 | "The shaft descended at a forty-five degree angle, concrete steps slick with moisture and something else, something that smelled faintly of copper and old herbs." | | 2 | "Her flashlight beam cut through the darkness, illuminating graffiti that seemed to shift at the edges of her vision." | | 3 | "Names written in languages that made her eyes water when she tried to focus on them." | | 4 | "The Market hummed with activity she couldn't begin to understand—whispers in languages that scraped against her skull, the rustle of wings that might have been …" |
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| 86.54% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 1 | | matches | | 0 | "Harlow kept, though her heart hammered against her ribs" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 1 | | fancyTags | | 0 | "The thin man hissed (hiss)" |
| | dialogueSentences | 39 | | tagDensity | 0.051 | | leniency | 0.103 | | rawRatio | 0.5 | | effectiveRatio | 0.051 | |