| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 16 | | adverbTagCount | 1 | | adverbTags | | 0 | "Miller moved back [back]" |
| | dialogueSentences | 43 | | tagDensity | 0.372 | | leniency | 0.744 | | rawRatio | 0.063 | | effectiveRatio | 0.047 | |
| 90.25% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1026 | | 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) | |
| 36.65% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1026 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "shattered" | | 1 | "crystalline" | | 2 | "dancing" | | 3 | "traced" | | 4 | "scanned" | | 5 | "database" | | 6 | "silence" | | 7 | "trembled" | | 8 | "echoed" | | 9 | "whisper" | | 10 | "depths" |
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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) | |
| 80.75% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 69 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 96 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 28 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1026 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 33 | | wordCount | 715 | | uniqueNames | 9 | | maxNameDensity | 1.96 | | worstName | "Quinn" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Quinn" | | discoveredNames | | Quinn | 14 | | Camden | 2 | | Tube | 1 | | Miller | 6 | | Victorian | 1 | | Morris | 1 | | London | 1 | | Kowalski | 1 | | Eva | 6 |
| | persons | | 0 | "Quinn" | | 1 | "Miller" | | 2 | "Victorian" | | 3 | "Morris" | | 4 | "Kowalski" | | 5 | "Eva" |
| | places | | | globalScore | 0.521 | | windowScore | 0.5 | |
| 97.92% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 48 | | glossingSentenceCount | 1 | | matches | | 0 | "sounded like a dozen people walking just o" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1026 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 96 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 45 | | mean | 22.8 | | std | 15.13 | | cv | 0.664 | | sampleLengths | | 0 | 27 | | 1 | 35 | | 2 | 21 | | 3 | 34 | | 4 | 5 | | 5 | 43 | | 6 | 9 | | 7 | 23 | | 8 | 6 | | 9 | 39 | | 10 | 61 | | 11 | 24 | | 12 | 5 | | 13 | 13 | | 14 | 15 | | 15 | 3 | | 16 | 39 | | 17 | 23 | | 18 | 60 | | 19 | 23 | | 20 | 41 | | 21 | 20 | | 22 | 36 | | 23 | 16 | | 24 | 15 | | 25 | 27 | | 26 | 2 | | 27 | 17 | | 28 | 21 | | 29 | 12 | | 30 | 43 | | 31 | 2 | | 32 | 25 | | 33 | 38 | | 34 | 5 | | 35 | 9 | | 36 | 27 | | 37 | 2 | | 38 | 37 | | 39 | 5 | | 40 | 25 | | 41 | 40 | | 42 | 32 | | 43 | 3 | | 44 | 18 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 69 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 110 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 1 | | flaggedSentences | 1 | | totalSentences | 96 | | ratio | 0.01 | | matches | | 0 | "No one had cut it out; instead, it lay on the damp concrete, shattered into blue crystalline shards like a dropped sapphire." |
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| 76.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 719 | | adjectiveStacks | 4 | | stackExamples | | 0 | "worn old brown leather" | | 1 | "dirty old rectangular green Victorian" | | 2 | "small rectangular cream-coloured paper" | | 3 | "beautiful small old round brass" |
| | adverbCount | 8 | | adverbRatio | 0.011126564673157162 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0027816411682892906 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 96 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 96 | | mean | 10.69 | | std | 6.73 | | cv | 0.63 | | sampleLengths | | 0 | 5 | | 1 | 22 | | 2 | 19 | | 3 | 16 | | 4 | 12 | | 5 | 9 | | 6 | 5 | | 7 | 16 | | 8 | 13 | | 9 | 5 | | 10 | 14 | | 11 | 12 | | 12 | 1 | | 13 | 12 | | 14 | 4 | | 15 | 5 | | 16 | 4 | | 17 | 19 | | 18 | 4 | | 19 | 6 | | 20 | 23 | | 21 | 5 | | 22 | 11 | | 23 | 13 | | 24 | 11 | | 25 | 18 | | 26 | 1 | | 27 | 2 | | 28 | 16 | | 29 | 7 | | 30 | 13 | | 31 | 4 | | 32 | 5 | | 33 | 11 | | 34 | 2 | | 35 | 8 | | 36 | 7 | | 37 | 3 | | 38 | 19 | | 39 | 20 | | 40 | 23 | | 41 | 3 | | 42 | 11 | | 43 | 28 | | 44 | 18 | | 45 | 6 | | 46 | 17 | | 47 | 4 | | 48 | 13 | | 49 | 3 |
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| 72.92% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.46875 | | totalSentences | 96 | | uniqueOpeners | 45 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 60 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 13 | | totalSentences | 60 | | matches | | 0 | "Her fingers, clad in thin" | | 1 | "She adjusted the worn old" | | 2 | "She moved away from the" | | 3 | "It clung to the underside" | | 4 | "She fished it out." | | 5 | "She reached into her coat" | | 6 | "Its face bore protective sigils," | | 7 | "It trembled, spinning in a" | | 8 | "Her heels clicked." | | 9 | "It was the currency of" | | 10 | "She did not turn." | | 11 | "Her eyes locked on the" | | 12 | "Her voice remained steady, though" |
| | ratio | 0.217 | |
| 10.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 54 | | totalSentences | 60 | | matches | | 0 | "The corpse lacked a tongue." | | 1 | "Harlow Quinn knelt beside the" | | 2 | "DC Miller said, his torchlight" | | 3 | "Quinn did not look up." | | 4 | "Her fingers, clad in thin" | | 5 | "Quinn stood up, her posture" | | 6 | "She adjusted the worn old" | | 7 | "The hands moved, but the" | | 8 | "Miller crouched, his boots squelching." | | 9 | "Quinn scanned the platform" | | 10 | "Quinn pointed her beam of" | | 11 | "A heavy signet ring glinted." | | 12 | "She moved away from the" | | 13 | "Dirt clung to the dirty" | | 14 | "The air smelled of old" | | 15 | "The same smell that had" | | 16 | "A sliver of paper caught" | | 17 | "It clung to the underside" | | 18 | "She fished it out." | | 19 | "Miller walked over, his torch" |
| | ratio | 0.9 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 60 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 29 | | technicalSentenceCount | 1 | | matches | | 0 | "The air smelled of old iron, coal dust, and a sharp, metallic sting that made her throat tickle." |
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| 31.25% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 16 | | uselessAdditionCount | 3 | | matches | | 0 | "Quinn stood up, her posture rigid with military precision" | | 1 | "Miller moved back, his boots drumming a fast beat on the iron steps" | | 2 | "Eva's voice dropped, her green eyes wide behind her spectacles" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 43 | | tagDensity | 0.093 | | leniency | 0.186 | | rawRatio | 0 | | effectiveRatio | 0 | |