| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 4 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 22 | | tagDensity | 0.182 | | leniency | 0.364 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 88.52% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1307 | | totalAiIsmAdverbs | 3 | | 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) | |
| 27.31% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1307 | | totalAiIsms | 19 | | found | | | highlights | | 0 | "calculated" | | 1 | "scanning" | | 2 | "rhythmic" | | 3 | "vibrated" | | 4 | "gloom" | | 5 | "weight" | | 6 | "velvet" | | 7 | "echoed" | | 8 | "synchronized" | | 9 | "whisper" | | 10 | "echoing" | | 11 | "hulking" | | 12 | "silence" | | 13 | "silk" |
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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 | 106 | | matches | | |
| 61.99% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 5 | | narrationSentences | 106 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 124 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 26 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1303 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 61.50% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 37 | | wordCount | 1130 | | uniqueNames | 12 | | maxNameDensity | 1.77 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Soho | 2 | | Harlow | 1 | | Quinn | 20 | | Tube | 1 | | Veil | 1 | | Market | 1 | | Camden | 1 | | Morris | 1 | | Saint | 1 | | Christopher | 1 | | Herrera | 1 | | Tomás | 6 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Morris" | | 3 | "Saint" | | 4 | "Christopher" | | 5 | "Herrera" | | 6 | "Tomás" |
| | places | | | globalScore | 0.615 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 84 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like wet parchment" |
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| 46.51% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.535 | | wordCount | 1303 | | matches | | 0 | "not in surrender, but in a heap" | | 1 | "not to help him, but to reclaim something" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 124 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 62 | | mean | 21.02 | | std | 16.68 | | cv | 0.793 | | sampleLengths | | 0 | 57 | | 1 | 50 | | 2 | 47 | | 3 | 10 | | 4 | 55 | | 5 | 11 | | 6 | 46 | | 7 | 4 | | 8 | 57 | | 9 | 3 | | 10 | 72 | | 11 | 27 | | 12 | 12 | | 13 | 6 | | 14 | 13 | | 15 | 8 | | 16 | 8 | | 17 | 3 | | 18 | 23 | | 19 | 12 | | 20 | 9 | | 21 | 44 | | 22 | 9 | | 23 | 34 | | 24 | 9 | | 25 | 8 | | 26 | 20 | | 27 | 42 | | 28 | 33 | | 29 | 11 | | 30 | 23 | | 31 | 36 | | 32 | 5 | | 33 | 7 | | 34 | 23 | | 35 | 12 | | 36 | 18 | | 37 | 2 | | 38 | 23 | | 39 | 9 | | 40 | 5 | | 41 | 32 | | 42 | 12 | | 43 | 10 | | 44 | 24 | | 45 | 6 | | 46 | 10 | | 47 | 8 | | 48 | 40 | | 49 | 22 |
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| 95.33% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 106 | | matches | | 0 | "was paid" | | 1 | "being dragged" | | 2 | "was gone" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 202 | | matches | (empty) | |
| 27.65% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 2 | | flaggedSentences | 5 | | totalSentences | 124 | | ratio | 0.04 | | matches | | 0 | "Twenty yards ahead, the suspect—a gaunt man in a grey duster—weaved through the midnight crowds." | | 1 | "He didn't run with panic; he moved with a calculated, gliding efficiency that defied the slickness of the ground." | | 2 | "The scent of rain vanished, replaced by something cloying—cinnamon, sulfur, and rotting lilies." | | 3 | "She had heard the whispers in the precinct—ghost stories told by veterans to scare rookies." | | 4 | "They didn't carry guns; they carried jagged shards of obsidian and vials of swirling green gas." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1139 | | adjectiveStacks | 1 | | stackExamples | | 0 | "heavy, pressing against her" |
| | adverbCount | 25 | | adverbRatio | 0.021949078138718173 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.006145741878841089 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 124 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 124 | | mean | 10.51 | | std | 5.56 | | cv | 0.529 | | sampleLengths | | 0 | 12 | | 1 | 11 | | 2 | 15 | | 3 | 19 | | 4 | 3 | | 5 | 17 | | 6 | 7 | | 7 | 4 | | 8 | 19 | | 9 | 16 | | 10 | 14 | | 11 | 17 | | 12 | 7 | | 13 | 3 | | 14 | 6 | | 15 | 11 | | 16 | 11 | | 17 | 6 | | 18 | 21 | | 19 | 10 | | 20 | 1 | | 21 | 14 | | 22 | 3 | | 23 | 13 | | 24 | 16 | | 25 | 4 | | 26 | 12 | | 27 | 14 | | 28 | 9 | | 29 | 22 | | 30 | 3 | | 31 | 2 | | 32 | 15 | | 33 | 26 | | 34 | 4 | | 35 | 25 | | 36 | 6 | | 37 | 3 | | 38 | 18 | | 39 | 12 | | 40 | 6 | | 41 | 6 | | 42 | 4 | | 43 | 3 | | 44 | 8 | | 45 | 8 | | 46 | 3 | | 47 | 10 | | 48 | 13 | | 49 | 12 |
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| 36.99% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 16 | | diversityRatio | 0.2845528455284553 | | totalSentences | 123 | | uniqueOpeners | 35 | |
| 97.09% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 103 | | matches | | 0 | "Then she looked at the" | | 1 | "Instead, she found herself staring" | | 2 | "Only the grey smoke remained," |
| | ratio | 0.029 | |
| 91.84% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 33 | | totalSentences | 103 | | matches | | 0 | "He didn't run with panic;" | | 1 | "She tightened her grip on" | | 2 | "She didn't shout for him" | | 3 | "She tracked the sway of" | | 4 | "She rounded the corner just" | | 5 | "She slammed her shoulder into" | | 6 | "It didn't budge." | | 7 | "She knelt, clicking her flashlight" | | 8 | "She checked the worn leather" | | 9 | "She hit the bottom with" | | 10 | "She had heard the whispers" | | 11 | "They spoke of a place" | | 12 | "She thought of Morris." | | 13 | "She thought of the vacant" | | 14 | "He hadn't run." | | 15 | "He waited by a stall" | | 16 | "He didn't look afraid." | | 17 | "He looked bored." | | 18 | "He stepped closer, the violet" | | 19 | "He reached into his pocket" |
| | ratio | 0.32 | |
| 13.40% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 92 | | totalSentences | 103 | | matches | | 0 | "Detective Harlow Quinn lunged forward," | | 1 | "He didn't run with panic;" | | 2 | "Quinn’s chest burned." | | 3 | "She tightened her grip on" | | 4 | "She didn't shout for him" | | 5 | "Breath was too precious." | | 6 | "She tracked the sway of" | | 7 | "The man bolted left, diving" | | 8 | "Quinn pivoted, her military precision" | | 9 | "She rounded the corner just" | | 10 | "She slammed her shoulder into" | | 11 | "It didn't budge." | | 12 | "Quinn stepped back, scanning the" | | 13 | "A narrow ventilation grate leaned" | | 14 | "A faint, rhythmic thrumming vibrated" | | 15 | "She knelt, clicking her flashlight" | | 16 | "The beam cut through the" | | 17 | "She checked the worn leather" | | 18 | "Quinn slid through the grate," | | 19 | "The air shifted." |
| | ratio | 0.893 | |
| 48.54% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 103 | | matches | | 0 | "Before her stretched an abandoned" |
| | ratio | 0.01 | |
| 95.24% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 60 | | technicalSentenceCount | 4 | | matches | | 0 | "He didn't run with panic; he moved with a calculated, gliding efficiency that defied the slickness of the ground." | | 1 | "The man bolted left, diving into an alleyway that smelled of wet cardboard and old grease." | | 2 | "They flowed like a tide of ink, their eyes glowing with a hunger that ignored the threat of lead." | | 3 | "He wore a stained medical coat and a Saint Christopher medallion that swung wildly against his olive skin." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 4 | | uselessAdditionCount | 1 | | matches | | 0 | "she commanded, her voice echoing in the void" |
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| 59.09% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 2 | | fancyTags | | 0 | "Tomás yelled (yell)" | | 1 | "Tomás roared (roar)" |
| | dialogueSentences | 22 | | tagDensity | 0.136 | | leniency | 0.273 | | rawRatio | 0.667 | | effectiveRatio | 0.182 | |