| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 37 | | tagDensity | 0.216 | | leniency | 0.432 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 88.15% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 844 | | totalAiIsmAdverbs | 2 | | 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) | |
| 46.68% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 844 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "perfect" | | 1 | "traced" | | 2 | "sentinels" | | 3 | "pulse" | | 4 | "magnetic" | | 5 | "standard" | | 6 | "warmth" | | 7 | "chaotic" | | 8 | "flickered" |
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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 | 69 | | matches | (empty) | |
| 18.63% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 5 | | narrationSentences | 69 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 98 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 25 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 4 | | totalWords | 843 | | ratio | 0.005 | | matches | | 0 | "You sound like Morris." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 12 | | unquotedAttributions | 1 | | matches | | 0 | "Early retirement, they called it." |
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| 4.28% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 33 | | wordCount | 549 | | uniqueNames | 11 | | maxNameDensity | 2.91 | | worstName | "Quinn" | | maxWindowNameDensity | 4 | | worstWindowName | "Quinn" | | discoveredNames | | Victorian | 2 | | British | 1 | | Museum | 1 | | Harlow | 1 | | Quinn | 16 | | Peters | 4 | | Morris | 3 | | Ashworth | 2 | | Verdigris | 1 | | October | 1 | | Latin | 1 |
| | persons | | 0 | "Victorian" | | 1 | "Museum" | | 2 | "Harlow" | | 3 | "Quinn" | | 4 | "Peters" | | 5 | "Morris" | | 6 | "Ashworth" | | 7 | "Verdigris" |
| | places | (empty) | | globalScore | 0.043 | | windowScore | 0.333 | |
| 0.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 40 | | glossingSentenceCount | 3 | | matches | | 0 | "patterns that seemed to shift when she wasn't looking directly" | | 1 | "seemed deeper than they should be" | | 2 | "quite meet properly" |
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| 81.38% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 1.186 | | wordCount | 843 | | matches | | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 98 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 49 | | mean | 17.2 | | std | 12.57 | | cv | 0.731 | | sampleLengths | | 0 | 31 | | 1 | 34 | | 2 | 31 | | 3 | 2 | | 4 | 23 | | 5 | 29 | | 6 | 4 | | 7 | 5 | | 8 | 42 | | 9 | 8 | | 10 | 9 | | 11 | 46 | | 12 | 3 | | 13 | 17 | | 14 | 14 | | 15 | 3 | | 16 | 25 | | 17 | 37 | | 18 | 14 | | 19 | 33 | | 20 | 13 | | 21 | 50 | | 22 | 7 | | 23 | 4 | | 24 | 26 | | 25 | 5 | | 26 | 3 | | 27 | 26 | | 28 | 24 | | 29 | 3 | | 30 | 24 | | 31 | 20 | | 32 | 6 | | 33 | 14 | | 34 | 16 | | 35 | 12 | | 36 | 2 | | 37 | 32 | | 38 | 14 | | 39 | 10 | | 40 | 4 | | 41 | 30 | | 42 | 5 | | 43 | 17 | | 44 | 20 | | 45 | 21 | | 46 | 13 | | 47 | 6 | | 48 | 6 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 69 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 98 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 98 | | ratio | 0 | | matches | (empty) | |
| 88.07% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 261 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 14 | | adverbRatio | 0.05363984674329502 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.011494252873563218 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 98 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 98 | | mean | 8.6 | | std | 5.14 | | cv | 0.598 | | sampleLengths | | 0 | 15 | | 1 | 2 | | 2 | 2 | | 3 | 12 | | 4 | 17 | | 5 | 13 | | 6 | 4 | | 7 | 13 | | 8 | 18 | | 9 | 2 | | 10 | 14 | | 11 | 9 | | 12 | 8 | | 13 | 10 | | 14 | 9 | | 15 | 2 | | 16 | 4 | | 17 | 5 | | 18 | 7 | | 19 | 5 | | 20 | 16 | | 21 | 14 | | 22 | 8 | | 23 | 9 | | 24 | 3 | | 25 | 11 | | 26 | 19 | | 27 | 3 | | 28 | 5 | | 29 | 5 | | 30 | 3 | | 31 | 8 | | 32 | 9 | | 33 | 14 | | 34 | 3 | | 35 | 25 | | 36 | 9 | | 37 | 4 | | 38 | 7 | | 39 | 9 | | 40 | 5 | | 41 | 1 | | 42 | 2 | | 43 | 14 | | 44 | 12 | | 45 | 8 | | 46 | 13 | | 47 | 13 | | 48 | 19 | | 49 | 21 |
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| 94.90% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.5816326530612245 | | totalSentences | 98 | | uniqueOpeners | 57 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 58 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 8 | | totalSentences | 58 | | matches | | 0 | "He'd never recovered." | | 1 | "She knew better." | | 2 | "Her breath began to fog," | | 3 | "She pointed to a sequence" | | 4 | "*You sound like Morris.*" | | 5 | "It was warm to the" | | 6 | "It matched the symbols in" | | 7 | "she called toward the corner" |
| | ratio | 0.138 | |
| 72.07% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 45 | | totalSentences | 58 | | matches | | 0 | "The chalk outline looked wrong" | | 1 | "Detective Harlow Quinn crouched beside" | | 2 | "This scene felt choreographed." | | 3 | "DS Peters said, flipping through" | | 4 | "Quinn stood, studying the reading" | | 5 | "The air tasted of old" | | 6 | "The desk held a single" | | 7 | "Quinn leaned closer without touching." | | 8 | "The pages were covered in" | | 9 | "Greek letters twisted into patterns" | | 10 | "Quinn's jaw tightened." | | 11 | "Peters had been her partner" | | 12 | "He'd never recovered." | | 13 | "She knew better." | | 14 | "Quinn walked to the desk" | | 15 | "The woman had simply collapsed" | | 16 | "Heart failure, the coroner suggested." | | 17 | "Quinn pointed to a small" | | 18 | "Verdigris clung to its edges" | | 19 | "The needle spun wildly, pointing" |
| | ratio | 0.776 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 58 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 23 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 37 | | tagDensity | 0.135 | | leniency | 0.27 | | rawRatio | 0 | | effectiveRatio | 0 | |