| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 118 | | tagDensity | 0.008 | | leniency | 0.017 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2236 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 75.40% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2236 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "charm" | | 1 | "grave" | | 2 | "pulse" | | 3 | "quivered" | | 4 | "trembled" | | 5 | "silence" | | 6 | "fluttered" | | 7 | "structure" | | 8 | "familiar" | | 9 | "shattered" |
| |
| 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 | 206 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 206 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 323 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 37 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2236 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 38.61% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 94 | | wordCount | 1616 | | uniqueNames | 15 | | maxNameDensity | 2.23 | | worstName | "Quinn" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 36 | | Veil | 3 | | Market | 1 | | Kowalski | 1 | | Harding | 8 | | Eva | 23 | | Venn | 9 | | Compass | 2 | | Halberg | 1 | | Threshold | 1 | | Anatomy | 1 | | Morris | 3 | | Whitechapel | 1 | | Four | 3 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Kowalski" | | 3 | "Harding" | | 4 | "Eva" | | 5 | "Venn" | | 6 | "Compass" | | 7 | "Halberg" | | 8 | "Morris" |
| | places | | | globalScore | 0.386 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 134 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 2236 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 323 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 222 | | mean | 10.07 | | std | 11.76 | | cv | 1.168 | | sampleLengths | | 0 | 6 | | 1 | 34 | | 2 | 2 | | 3 | 15 | | 4 | 10 | | 5 | 54 | | 6 | 12 | | 7 | 4 | | 8 | 1 | | 9 | 3 | | 10 | 4 | | 11 | 17 | | 12 | 2 | | 13 | 34 | | 14 | 19 | | 15 | 4 | | 16 | 3 | | 17 | 3 | | 18 | 3 | | 19 | 32 | | 20 | 4 | | 21 | 3 | | 22 | 7 | | 23 | 4 | | 24 | 12 | | 25 | 9 | | 26 | 1 | | 27 | 56 | | 28 | 9 | | 29 | 4 | | 30 | 3 | | 31 | 3 | | 32 | 4 | | 33 | 8 | | 34 | 4 | | 35 | 10 | | 36 | 6 | | 37 | 8 | | 38 | 6 | | 39 | 4 | | 40 | 6 | | 41 | 4 | | 42 | 5 | | 43 | 26 | | 44 | 7 | | 45 | 1 | | 46 | 7 | | 47 | 2 | | 48 | 8 | | 49 | 3 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 206 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 261 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 323 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1617 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 17 | | adverbRatio | 0.010513296227581941 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0012368583797155227 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 323 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 323 | | mean | 6.92 | | std | 4.78 | | cv | 0.69 | | sampleLengths | | 0 | 6 | | 1 | 14 | | 2 | 20 | | 3 | 2 | | 4 | 11 | | 5 | 2 | | 6 | 1 | | 7 | 1 | | 8 | 10 | | 9 | 12 | | 10 | 14 | | 11 | 9 | | 12 | 4 | | 13 | 15 | | 14 | 12 | | 15 | 4 | | 16 | 1 | | 17 | 3 | | 18 | 4 | | 19 | 17 | | 20 | 2 | | 21 | 11 | | 22 | 13 | | 23 | 6 | | 24 | 4 | | 25 | 11 | | 26 | 8 | | 27 | 4 | | 28 | 3 | | 29 | 3 | | 30 | 3 | | 31 | 10 | | 32 | 6 | | 33 | 16 | | 34 | 4 | | 35 | 3 | | 36 | 7 | | 37 | 4 | | 38 | 12 | | 39 | 9 | | 40 | 1 | | 41 | 8 | | 42 | 17 | | 43 | 10 | | 44 | 21 | | 45 | 9 | | 46 | 4 | | 47 | 3 | | 48 | 3 | | 49 | 4 |
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| 55.11% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.35294117647058826 | | totalSentences | 323 | | uniqueOpeners | 114 | |
| 54.35% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 184 | | matches | | 0 | "Instead, it ran from the" | | 1 | "Only cables, flaking tiles and" | | 2 | "Then she saw the fibres." |
| | ratio | 0.016 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 26 | | totalSentences | 184 | | matches | | 0 | "His paper overshoes skidded across" | | 1 | "He pointed towards an iron" | | 2 | "His mouth tightened." | | 3 | "Her curly red hair had" | | 4 | "It formed no circle." | | 5 | "She crouched near the body." | | 6 | "His eyes remained shut." | | 7 | "It pierced several folded layers" | | 8 | "She touched its edge with" | | 9 | "It clung in a glossy" | | 10 | "She pressed two fingers to" | | 11 | "She lifted his wrist." | | 12 | "She lifted the compass by" | | 13 | "She moved it past his" | | 14 | "She looked at the coat" | | 15 | "Its hem rested beneath his" | | 16 | "Her gaze travelled to the" | | 17 | "She held the Veil Compass" | | 18 | "She pressed her torch close." | | 19 | "Her fingers closed around the" |
| | ratio | 0.141 | |
| 57.83% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 148 | | totalSentences | 184 | | matches | | 0 | "Detective Harlow Quinn caught the" | | 1 | "His paper overshoes skidded across" | | 2 | "The abandoned station swallowed her" | | 3 | "Canvas stalls crowded the old" | | 4 | "Glass jars held teeth, feathers" | | 5 | "Copper cages hung from hooks" | | 6 | "Each cage stood open." | | 7 | "A ticket booth squatted at" | | 8 | "Quinn released the constable." | | 9 | "He pointed towards an iron" | | 10 | "A length of chain hung" | | 11 | "The padlock remained closed." | | 12 | "Quinn studied the gap where" | | 13 | "Someone had unthreaded it without" | | 14 | "His mouth tightened." | | 15 | "Quinn checked the worn leather" | | 16 | "A camera shutter clicked." | | 17 | "The crime scene photographer lowered" | | 18 | "A soft voice rose behind" | | 19 | "Eva Kowalski stepped out with" |
| | ratio | 0.804 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 184 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 60 | | technicalSentenceCount | 1 | | matches | | 0 | "Glass jars held teeth, feathers and pale things that contracted when torchlight touched them." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 118 | | tagDensity | 0.008 | | leniency | 0.017 | | rawRatio | 1 | | effectiveRatio | 0.017 | |