| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 20 | | adverbTagCount | 1 | | adverbTags | | 0 | "she noted aloud [aloud]" |
| | dialogueSentences | 39 | | tagDensity | 0.513 | | leniency | 1 | | rawRatio | 0.05 | | effectiveRatio | 0.05 | |
| 85.19% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1350 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "sharply" | | 1 | "lazily" | | 2 | "slightly" | | 3 | "gently" |
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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) | |
| 59.26% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1350 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "silence" | | 1 | "scanned" | | 2 | "gloom" | | 3 | "etched" | | 4 | "throbbed" | | 5 | "shimmered" | | 6 | "measured" | | 7 | "racing" | | 8 | "intricate" | | 9 | "stomach" | | 10 | "tangible" |
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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 | 85 | | matches | (empty) | |
| 92.44% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 85 | | filterMatches | | | hedgeMatches | | |
| 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 | | maxSentenceWordsSeen | 35 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1347 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 17 | | unquotedAttributions | 0 | | matches | (empty) | |
| 34.54% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 51 | | wordCount | 996 | | uniqueNames | 10 | | maxNameDensity | 2.31 | | worstName | "Harlow" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Harlow" | | discoveredNames | | Camden | 1 | | Harlow | 23 | | Quinn | 2 | | Tube | 1 | | Met | 1 | | Kowalski | 1 | | Eva | 15 | | Morris | 3 | | Veil | 1 | | Market | 3 |
| | persons | | 0 | "Camden" | | 1 | "Harlow" | | 2 | "Quinn" | | 3 | "Met" | | 4 | "Kowalski" | | 5 | "Eva" | | 6 | "Morris" |
| | places | (empty) | | globalScore | 0.345 | | windowScore | 0.5 | |
| 27.05% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 61 | | glossingSentenceCount | 3 | | matches | | 0 | "felt like it was holding its breath" | | 1 | "looked like the usual tagger scrawl—names" | | 2 | "seemed deeper than it should be, swallowing the light from the floodlamps" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.742 | | wordCount | 1347 | | matches | | 0 | "not of fear, but of rapturous awe, his pupils dilated so wide the iris was ne" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 104 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 34 | | mean | 39.62 | | std | 19.82 | | cv | 0.5 | | sampleLengths | | 0 | 85 | | 1 | 62 | | 2 | 15 | | 3 | 72 | | 4 | 35 | | 5 | 45 | | 6 | 66 | | 7 | 14 | | 8 | 74 | | 9 | 25 | | 10 | 34 | | 11 | 68 | | 12 | 22 | | 13 | 59 | | 14 | 34 | | 15 | 51 | | 16 | 18 | | 17 | 24 | | 18 | 41 | | 19 | 45 | | 20 | 15 | | 21 | 36 | | 22 | 43 | | 23 | 27 | | 24 | 27 | | 25 | 53 | | 26 | 18 | | 27 | 19 | | 28 | 36 | | 29 | 9 | | 30 | 44 | | 31 | 23 | | 32 | 43 | | 33 | 65 |
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| 84.62% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 85 | | matches | | 0 | "was frozen" | | 1 | "were curled" | | 2 | "were locked" | | 3 | "was etched" | | 4 | "were repeated" | | 5 | "been forced" |
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| 12.73% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 5 | | totalVerbs | 178 | | matches | | 0 | "was holding" | | 1 | "was crouching" | | 2 | "wasn't pointing" | | 3 | "was spinning" | | 4 | "was bleeding" |
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| 32.97% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 1 | | flaggedSentences | 4 | | totalSentences | 104 | | ratio | 0.038 | | matches | | 0 | "The face was etched with symbols that hurt Harlow's eyes if she stared at them too long—protective sigils, though she didn't know the word for them yet." | | 1 | "At first glance, it looked like the usual tagger scrawl—names, dates, crude drawings." | | 2 | "The lack of defensive wounds, the look of awe—it suggested he had walked willingly into whatever happened here." | | 3 | "The binding runes on the wall weren't to protect the station from the outside; they were to anchor the Market to this specific location prematurely." |
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| 88.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1004 | | adjectiveStacks | 2 | | stackExamples | | 0 | "heavy, pressing against her" | | 1 | "small, bone-white token," |
| | adverbCount | 28 | | adverbRatio | 0.027888446215139442 | | lyAdverbCount | 12 | | lyAdverbRatio | 0.01195219123505976 | |
| 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 | 12.95 | | std | 8.21 | | cv | 0.634 | | sampleLengths | | 0 | 22 | | 1 | 23 | | 2 | 12 | | 3 | 28 | | 4 | 24 | | 5 | 22 | | 6 | 16 | | 7 | 10 | | 8 | 5 | | 9 | 2 | | 10 | 21 | | 11 | 20 | | 12 | 29 | | 13 | 6 | | 14 | 16 | | 15 | 13 | | 16 | 27 | | 17 | 18 | | 18 | 5 | | 19 | 28 | | 20 | 4 | | 21 | 5 | | 22 | 24 | | 23 | 8 | | 24 | 6 | | 25 | 5 | | 26 | 15 | | 27 | 17 | | 28 | 27 | | 29 | 5 | | 30 | 5 | | 31 | 14 | | 32 | 11 | | 33 | 12 | | 34 | 22 | | 35 | 6 | | 36 | 10 | | 37 | 26 | | 38 | 26 | | 39 | 11 | | 40 | 11 | | 41 | 10 | | 42 | 13 | | 43 | 7 | | 44 | 4 | | 45 | 4 | | 46 | 21 | | 47 | 8 | | 48 | 26 | | 49 | 8 |
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| 59.55% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.39805825242718446 | | totalSentences | 103 | | uniqueOpeners | 41 | |
| 41.67% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 80 | | matches | | 0 | "Somewhere in that blackness, a" |
| | ratio | 0.013 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 20 | | totalSentences | 80 | | matches | | 0 | "She adjusted the worn leather" | | 1 | "She moved with military precision," | | 2 | "His face was frozen in" | | 3 | "They were curled inward, clutching" | | 4 | "It was spinning lazily, counter-clockwise." | | 5 | "She hated when Eva slipped" | | 6 | "It reminded her too much" | | 7 | "They formed a perimeter." | | 8 | "She walked the perimeter, her" | | 9 | "Her breath plumed in front" | | 10 | "she noted aloud, more to" | | 11 | "It was the scent of" | | 12 | "She returned to the body," | | 13 | "He was a participant." | | 14 | "She withdrew a small, bone-white" | | 15 | "She looked down the dark" | | 16 | "She checked her watch." | | 17 | "she gestured to the body," | | 18 | "She turned toward the tunnel," | | 19 | "She stepped past the yellow" |
| | ratio | 0.25 | |
| 35.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 68 | | totalSentences | 80 | | matches | | 0 | "The air beneath Camden tasted" | | 1 | "Detective Harlow Quinn stood at" | | 2 | "The silence here was heavy," | | 3 | "She adjusted the worn leather" | | 4 | "The floodlights set up by" | | 5 | "a voice called out, too" | | 6 | "Eva Kowalski was crouching near" | | 7 | "The younger woman pushed her" | | 8 | "Eva clutched a worn leather" | | 9 | "Harlow said, her voice clipped" | | 10 | "She moved with military precision," | | 11 | "Eva said, tucking a stray" | | 12 | "Harlow knelt beside the body." | | 13 | "The victim was a man" | | 14 | "His face was frozen in" | | 15 | "Eva whispered, leaning in" | | 16 | "Harlow examined the man's fingers." | | 17 | "They were curled inward, clutching" | | 18 | "The face was etched with" | | 19 | "The needle wasn't pointing north." |
| | ratio | 0.85 | |
| 62.50% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 80 | | matches | | | ratio | 0.013 | |
| 3.97% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 36 | | technicalSentenceCount | 7 | | matches | | 0 | "The air beneath Camden tasted of wet rust and ancient dust, a flavor that had nothing to do with the city above." | | 1 | "The floodlights set up by uniformed officers cast long, jagged shadows against the peeling advertisements for concerts that hadn't happened in decades." | | 2 | "Eva clutched a worn leather satchel to her chest as if it contained the crown jewels, though Harlow knew it was likely filled with arcane texts and research not…" | | 3 | "The victim was a man in his thirties, dressed in clothes that looked expensive but strangely outdated, as if pulled from a charity bin specializing in the 1920s…" | | 4 | "Specific symbols were repeated at regular intervals along the tunnel walls, painted in a pigment that shimmered faintly under the floodlights." | | 5 | "Morris had chased whispers of an underground market that moved with the moon, selling things that shouldn't exist." | | 6 | "She stepped past the yellow tape, her shadow stretching long and thin against the graffiti-covered walls, walking into the mystery that had claimed so much alre…" |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 20 | | uselessAdditionCount | 7 | | matches | | 0 | "Harlow said, her voice clipped" | | 1 | "Eva said, her voice dropping to a hush" | | 2 | "Eva insisted, her freckled complexion flushing" | | 3 | "she noted aloud, more to herself than to Eva" | | 4 | "Harlow said, her voice low and dangerous," | | 5 | "Eva asked, her green eyes fearful" | | 6 | "Harlow commanded, her bearing snapping back into command mode" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 17 | | fancyCount | 10 | | fancyTags | | 0 | "a voice called out (call out)" | | 1 | "Eva whispered (whisper)" | | 2 | "Harlow murmured (murmur)" | | 3 | "Eva insisted (insist)" | | 4 | "Eva explained (explain)" | | 5 | "she noted aloud (note)" | | 6 | "Eva added (add)" | | 7 | "Harlow ordered (order)" | | 8 | "she breathed (breathe)" | | 9 | "Harlow deduced (deduce)" |
| | dialogueSentences | 39 | | tagDensity | 0.436 | | leniency | 0.872 | | rawRatio | 0.588 | | effectiveRatio | 0.513 | |