| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 19 | | adverbTagCount | 1 | | adverbTags | | 0 | "The words tasted like [like]" |
| | dialogueSentences | 31 | | tagDensity | 0.613 | | leniency | 1 | | rawRatio | 0.053 | | effectiveRatio | 0.053 | |
| 80.73% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1038 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "perfectly" | | 1 | "slightly" | | 2 | "carefully" | | 3 | "suddenly" |
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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) | |
| 32.56% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1038 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "standard" | | 1 | "velvet" | | 2 | "echoing" | | 3 | "gloom" | | 4 | "etched" | | 5 | "intricate" | | 6 | "trembled" | | 7 | "rhythmic" | | 8 | "vibrated" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 101 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 101 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 114 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 28 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 3 | | markdownWords | 13 | | totalWords | 1038 | | ratio | 0.013 | | matches | | 0 | "One compass of seeking. For the Detective’s shadow. Paid in full." | | 1 | "The" | | 2 | "E.K." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 92.13% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 28 | | wordCount | 864 | | uniqueNames | 9 | | maxNameDensity | 1.16 | | worstName | "Davies" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 9 | | Tube | 1 | | Compasses | 1 | | Detective | 2 | | Davies | 10 | | Morris | 2 | | London | 1 | | Initials | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Detective" | | 3 | "Davies" | | 4 | "Morris" |
| | places | | | globalScore | 0.921 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 58 | | glossingSentenceCount | 1 | | matches | | 0 | "note that seemed to resonate in the bones of her skull" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.963 | | wordCount | 1038 | | matches | | 0 | "not rot, but a heavy, sweet odour, like burnt cinnamon mixed with somethi" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 114 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 32 | | mean | 32.44 | | std | 28.27 | | cv | 0.871 | | sampleLengths | | 0 | 64 | | 1 | 20 | | 2 | 61 | | 3 | 15 | | 4 | 98 | | 5 | 22 | | 6 | 5 | | 7 | 38 | | 8 | 2 | | 9 | 56 | | 10 | 10 | | 11 | 68 | | 12 | 10 | | 13 | 31 | | 14 | 2 | | 15 | 56 | | 16 | 18 | | 17 | 100 | | 18 | 13 | | 19 | 64 | | 20 | 44 | | 21 | 38 | | 22 | 7 | | 23 | 1 | | 24 | 2 | | 25 | 10 | | 26 | 42 | | 27 | 3 | | 28 | 73 | | 29 | 5 | | 30 | 22 | | 31 | 38 |
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| 98.32% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 101 | | matches | | 0 | "were draped" | | 1 | "was clenched" |
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| 14.81% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 144 | | matches | | 0 | "was seeing" | | 1 | "were beginning" | | 2 | "wasn’t looking" | | 3 | "was looking" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 114 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 395 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 4 | | adverbRatio | 0.010126582278481013 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.005063291139240506 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 114 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 114 | | mean | 9.11 | | std | 6.59 | | cv | 0.723 | | sampleLengths | | 0 | 11 | | 1 | 19 | | 2 | 6 | | 3 | 4 | | 4 | 3 | | 5 | 21 | | 6 | 8 | | 7 | 3 | | 8 | 9 | | 9 | 11 | | 10 | 19 | | 11 | 8 | | 12 | 17 | | 13 | 6 | | 14 | 15 | | 15 | 2 | | 16 | 3 | | 17 | 12 | | 18 | 6 | | 19 | 18 | | 20 | 3 | | 21 | 7 | | 22 | 19 | | 23 | 28 | | 24 | 6 | | 25 | 12 | | 26 | 4 | | 27 | 2 | | 28 | 3 | | 29 | 17 | | 30 | 1 | | 31 | 16 | | 32 | 4 | | 33 | 2 | | 34 | 19 | | 35 | 4 | | 36 | 5 | | 37 | 8 | | 38 | 13 | | 39 | 4 | | 40 | 3 | | 41 | 8 | | 42 | 2 | | 43 | 9 | | 44 | 11 | | 45 | 2 | | 46 | 2 | | 47 | 5 | | 48 | 8 | | 49 | 2 |
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| 56.14% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 11 | | diversityRatio | 0.39473684210526316 | | totalSentences | 114 | | uniqueOpeners | 45 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 88 | | matches | (empty) | | ratio | 0 | |
| 88.18% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 29 | | totalSentences | 88 | | matches | | 0 | "He was new." | | 1 | "It clung to the back" | | 2 | "Her knees popped." | | 3 | "She took in the broader" | | 4 | "they were a patchwork of" | | 5 | "She pulled on a nitrile" | | 6 | "She swept her torch to" | | 7 | "They were for" | | 8 | "His left hand was clenched." | | 9 | "She knelt again, carefully prying" | | 10 | "She recognised the style." | | 11 | "She held it up." | | 12 | "It pointed from the corpse," | | 13 | "She nodded to the burns" | | 14 | "She remembered Morris, three years" | | 15 | "He’d called it a" | | 16 | "She’d called it a psychotic" | | 17 | "She turned the compass over" | | 18 | "She pulled out her phone," | | 19 | "She wasn’t looking at the" |
| | ratio | 0.33 | |
| 45.23% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 73 | | totalSentences | 88 | | matches | | 0 | "The body lay across a" | | 1 | "Detective Harlow Quinn crouched, her" | | 2 | "The light caught the victim’s" | | 3 | "A series of perfectly spaced," | | 4 | "Davies asked from behind her" | | 5 | "He was new." | | 6 | "A good nose for blood," | | 7 | "Quinn didn’t look up" | | 8 | "The scent hit her next:" | | 9 | "It clung to the back" | | 10 | "The market stalls around them" | | 11 | "This place reeked of bad" | | 12 | "Davies suggested, his voice echoing" | | 13 | "Her knees popped." | | 14 | "She took in the broader" | | 15 | "The abandoned Tube station stretched" | | 16 | "they were a patchwork of" | | 17 | "She pulled on a nitrile" | | 18 | "Quinn pointed her torch at" | | 19 | "She swept her torch to" |
| | ratio | 0.83 | |
| 56.82% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 88 | | matches | | 0 | "Now, standing in a magical" |
| | ratio | 0.011 | |
| 31.25% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 32 | | technicalSentenceCount | 5 | | matches | | 0 | "Leather-bound books with titles in languages that made her eyes water, cages of iridescent feathers, shelves of glittering vials." | | 1 | "And the customers, those who hadn’t fled at the first sign of blue lights, watched from the shadows with eyes that reflected the torchlight in odd, pupil-less w…" | | 2 | "The way he’d looked at her at the end, as if he was seeing something right behind her." | | 3 | "Now, standing in a magical black market built in the guts of London, holding a compass that pointed at her personal darkness, she wasn’t sure what she believed." | | 4 | "At its centre, where a face should be, was a smooth, polished surface that reflected the torchlight back at her in a cold, white glare." |
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| 19.74% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 19 | | uselessAdditionCount | 4 | | matches | | 0 | "Davies suggested, his voice echoing slightly in the vast, tiled space" | | 1 | "Davies said, his professional demeanour fraying" | | 2 | "Davies said, a note of genuine unease in his voice" | | 3 | "she said, her voice dangerously calm" |
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| 53.23% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 8 | | fancyCount | 3 | | fancyTags | | 0 | "Davies suggested (suggest)" | | 1 | "Quinn murmured (murmur)" | | 2 | "Davies whispered (whisper)" |
| | dialogueSentences | 31 | | tagDensity | 0.258 | | leniency | 0.516 | | rawRatio | 0.375 | | effectiveRatio | 0.194 | |